{"id":227133,"date":"2026-07-25T17:16:19","date_gmt":"2026-07-25T17:16:19","guid":{"rendered":"https:\/\/www.9senses.ai\/?page_id=227133"},"modified":"2026-08-27T12:24:07","modified_gmt":"2026-08-27T12:24:07","slug":"what-is-ai","status":"publish","type":"page","link":"https:\/\/www.9senses.ai\/de\/what-is-ai\/","title":{"rendered":"What AI really is&#8230;"},"content":{"rendered":"<div class=\"et_pb_section_0 et_pb_section et_section_regular et_block_section\">\n<div class=\"et_pb_row_0 et_pb_row et_block_row ns-hdr\">\n<div class=\"et_pb_column_0 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough\">\n<div class=\"et_pb_text_0 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module ns-eyebrow\"><div class=\"et_pb_text_inner\"><p>9senses on artificial intelligence<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_1 et_pb_row et_flex_row ns-hdr\">\n<div class=\"et_pb_column_1 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_post_title_0 et_pb_post_title et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_title_container\"><h1 class=\"entry-title\">What AI really is\u2026<\/h1><\/div><\/div>\n\n<div class=\"et_pb_text_1 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><p>When most of us at 9senses began working with what is now labeled <strong>Artificial Intelligence,<\/strong> we didn't use that term. Back then, we were talking about non-linear computing, fuzzy logic, heuristics, machine learning, among others.<\/p>\n<p>Today, many people think that AI makes computers as smart as humans. In reality, computer software is still far away from reaching that level, but today it is able to <a href=\"\/why-9senses\">emulate and even surpass human capabilities in specific fields<\/a>, particularly those that require the processing of large amounts of information or the generation of output from a large data pool. We would like to instill a bit of clarity here, at the cost of taking some of the magic of AI away, as did Joseph Weizenbaum, the legendary creator of <a href=\"#eliza\">Eliza:<\/a><\/p>\n<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_2 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_code_0 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\"><div class=\"ns-vmap-editor-note\" style=\"position:relative;width:100%;overflow:hidden;aspect-ratio:5\/4;max-height:230px;\"><div style=\"position:absolute;inset:0;display:flex;align-items:center;justify-content:center;pointer-events:none\"><div style=\"padding:10px 12px;border:1px dashed rgba(170,180,205,.55);border-radius:6px;color:#8a93a6;font:600 12px\/1.4 sans-serif;background:rgba(8,13,25,.46)\"><div style=\"margin-bottom:6px\">Vector map \u2014 Main<\/div><code style=\"display:inline-block;padding:3px 6px;border-radius:4px;background:rgba(127,140,170,.12);color:inherit\"><div class=\"ns-vmap-editor-note\" style=\"position:relative;width:100%;overflow:hidden;aspect-ratio:5\/4;max-height:230px;\"><div style=\"position:absolute;inset:0;display:flex;align-items:center;justify-content:center;pointer-events:none\"><div style=\"padding:10px 12px;border:1px dashed rgba(170,180,205,.55);border-radius:6px;color:#8a93a6;font:600 12px\/1.4 sans-serif;background:rgba(8,13,25,.46)\"><div style=\"margin-bottom:6px\">Vector map \u2014 Main<\/div><code style=\"display:inline-block;padding:3px 6px;border-radius:4px;background:rgba(127,140,170,.12);color:inherit\">[ninesenses_vectormap #1]<\/code><div style=\"margin-top:6px;font-weight:400\">Max height: 230px. Preview on the live page.<\/div><\/div><\/div><\/div><\/code><div style=\"margin-top:6px;font-weight:400\">Max height: 230px. Preview on the live page.<\/div><\/div><\/div><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_1 et_pb_section et_section_regular et_block_section\">\n<div class=\"et_pb_row_2 et_pb_row et_block_row ns-quote\">\n<div class=\"et_pb_column_3 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough\">\n<div class=\"et_pb_text_2 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><blockquote style=\"border-left:0;padding-left:0;margin:30px 0 8px 0\"><p>\u201cWhat I had not realized is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.\u201d<\/p><\/blockquote>\n<p><span>Joseph Weizenbaum (1923-2008), Inventor of Eliza<\/span><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_2 et_pb_section et_section_regular et_block_section ns-block\" id=\"History_of_AI\" style=\"max-width:1080px;margin-left:auto;margin-right:auto;border-radius:0;hyphens:auto;-webkit-hyphens:auto;-ms-hyphens:auto\" lang=\"en\">\n<div class=\"et_pb_row_3 et_pb_row et_block_row ns-prose\">\n<div class=\"et_pb_column_4 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough\">\n<div class=\"et_pb_text_3 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><h2 style=\"display: inline; margin: 0 0.6em 0 0; padding: 0;\">History of AI<\/h2>\n<p><span>The idea of a machine-driven intelligence is not new. Literature has come up with speaking automatons way before the steam engine was invented, and since the arrival of computers, we have hoped for and <a href=\"\/can-ai-end-humanity\">feared AI smarter than humans<\/a>.<\/span><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_4 et_pb_row et_block_row ns-widget\">\n<div class=\"et_pb_column_5 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough\">\n<div class=\"et_pb_code_1 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\">\t<div id=\"ns-aih-zF2A2rh\" class=\"ns-aih ns-aih-theme-dark\"\n\t\tdata-autoplay=\"yes\"\n\t\tdata-interval=\"8000\"\n\t\tdata-start=\"0\"\n\t\tstyle=\"--ns-aih-accent:#58a7f9;--ns-aih-secondary:#0c71c3;--ns-aih-pane-min:240px;\">\n\n\t\t<div class=\"ns-aih-strip-wrap\">\n\t\t\t<div class=\"ns-aih-rail\" role=\"tablist\" aria-label=\"AI history milestones\">\n\t\t\t\t<div class=\"ns-aih-rail-track\">\n\t\t\t\t\t<div class=\"ns-aih-rail-line\" aria-hidden=\"true\"><\/div>\n\t\t\t\t\t<canvas class=\"ns-aih-rail-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot is-active\"\n\t\t\t\t\t\t\tdata-index=\"0\"\n\t\t\t\t\t\t\tstyle=\"left:0%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"true\"\n\t\t\t\t\t\t\taria-label=\"1816 - Fiction\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">1816<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"1\"\n\t\t\t\t\t\t\tstyle=\"left:49.556%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"1950 - The Turing Test\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">1950<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"2\"\n\t\t\t\t\t\t\tstyle=\"left:60.317%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"1966 - Eliza\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">1966<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"3\"\n\t\t\t\t\t\t\tstyle=\"left:73.097%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"1980s - Machine Learning\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">1980s<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"4\"\n\t\t\t\t\t\t\tstyle=\"left:79.822%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"1990s - Playing Chess (and Winning)\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">1990s<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"5\"\n\t\t\t\t\t\t\tstyle=\"left:86.548%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"2000s - Seeing and Knowing\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">2000s<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"6\"\n\t\t\t\t\t\t\tstyle=\"left:93.274%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"2010s - Solving Complex Problems\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">2010s<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\"\n\t\t\t\t\t\t\tclass=\"ns-aih-dot\"\n\t\t\t\t\t\t\tdata-index=\"7\"\n\t\t\t\t\t\t\tstyle=\"left:100%\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"2020s - Listening and Speaking\">\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-core\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t<span class=\"ns-aih-dot-year\">2020s<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<button type=\"button\" class=\"ns-aih-playtoken\" aria-pressed=\"true\">\n\t\t\t\t\t<span class=\"ns-aih-icon-play\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t<span class=\"ns-aih-icon-pause\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t<span class=\"ns-aih-visually-hidden ns-aih-label-play\">Play<\/span>\n\t\t\t\t\t<span class=\"ns-aih-visually-hidden ns-aih-label-pause\">Pause<\/span>\n\t\t\t\t<\/button>\n\t\t\t<\/div>\n\t\t<\/div>\n\n\t\t<div class=\"ns-aih-pane\">\n\t\t\t<div class=\"ns-aih-slides\">\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide is-active\" data-index=\"0\" aria-hidden=\"false\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Fiction<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--automaton\"\n        id=\"ns-aih-zF2A2rh-0-automaton\"\n        data-aihm-scene=\"automaton\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<figure class=\"aihm-visual aihm-automaton\" aria-label=\"Close view of the Jaquet-Droz Writer automaton moving its writing hand, quill, and head above the writing surface\">\n\t\t<img\n\t\t\tclass=\"aihm-automaton-image\"\n\t\t\tsrc=\"https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/automaton-writer-poster-v032.webp\"\n\t\t\tdata-aihm-poster-src=\"https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/automaton-writer-poster-v032.webp\"\n\t\t\tdata-aihm-motion-src=\"https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/automaton-writer-motion-v032.webp\"\t\t\talt=\"The Jaquet-Droz Writer automaton with its writing surface, quill, and hands in view\"\n\t\t\tloading=\"lazy\"\n\t\t\tdecoding=\"async\"\n\t\t>\n\t\t<figcaption class=\"aihm-credit\">\n\t\t\t<a class=\"aihm-credit-link\" href=\"https:\/\/commons.wikimedia.org\/wiki\/File:Jaquet_Droz_automata_-_Writer.jpg\" target=\"_blank\" rel=\"noopener noreferrer nofollow\" aria-label=\"View image credit and license details on Wikimedia Commons\">Image credit &amp; license<\/a>\n\t\t<\/figcaption>\n\t<\/figure>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">The idea of &quot;automatons&quot; acting &quot;intelligent&quot; is much older than computers themselves. For example, in E.T.A. Hoffmann&#039;s &quot;The Sandman&quot;, published in 1816, a beautiful girl named Olimpia is introduced. She dances and sings beautifully, but only speaks a few words. In fact, she is an automaton, created by physics professor Spalanzani.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">The Turing Test<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--turing\"\n        id=\"ns-aih-zF2A2rh-1-turing\"\n        data-aihm-scene=\"turing\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-vector-scene aihm-turing-preview\" role=\"img\" aria-label=\"Animated diagram of an interrogator exchanging text messages with two concealed respondents\">\n\t\t<svg class=\"aihm-vector-svg\" viewBox=\"0 0 640 360\" preserveAspectRatio=\"xMidYMid meet\" aria-hidden=\"true\" focusable=\"false\">\n\t\t\t<defs>\n\t\t\t\t<radialGradient 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fill=\"url(#ns-aih-zF2A2rh-1-turing-t-screen)\"\/>\n\t\t\t\t<rect x=\"392\" y=\"52\" width=\"176\" height=\"104\" class=\"aihm-terminal-outline\"\/>\n\t\t\t\t<circle cx=\"419\" cy=\"80\" r=\"10\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-blue)\" filter=\"url(#ns-aih-zF2A2rh-1-turing-t-glow)\"\/>\n\t\t\t\t<text class=\"aihm-terminal-letter\" x=\"419\" y=\"85\" text-anchor=\"middle\">B<\/text>\n\t\t\t\t<text class=\"aihm-terminal-title\" x=\"441\" y=\"83\">respondent<\/text>\n\t\t\t\t<line class=\"aihm-terminal-rule\" x1=\"412\" y1=\"103\" x2=\"546\" y2=\"103\"\/>\n\t\t\t\t<line class=\"aihm-terminal-rule aihm-terminal-rule--short\" x1=\"412\" y1=\"119\" x2=\"525\" y2=\"119\"\/>\n\t\t\t\t<line class=\"aihm-terminal-rule aihm-terminal-rule--reply\" x1=\"412\" y1=\"135\" x2=\"539\" y2=\"135\"\/>\n\t\t\t<\/g>\n\n\t\t\t<g class=\"aihm-turing-terminal aihm-turing-terminal--judge\">\n\t\t\t\t<rect x=\"226\" y=\"260\" width=\"188\" height=\"70\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-screen)\"\/>\n\t\t\t\t<rect x=\"226\" y=\"260\" width=\"188\" height=\"70\" class=\"aihm-terminal-outline\"\/>\n\t\t\t\t<text class=\"aihm-terminal-title aihm-terminal-title--judge\" x=\"320\" y=\"283\" text-anchor=\"middle\">interrogator<\/text>\n\t\t\t\t<text class=\"aihm-turing-choice\" x=\"320\" y=\"313\" text-anchor=\"middle\">A&nbsp;&nbsp;&nbsp;?&nbsp;&nbsp;&nbsp;B<\/text>\n\t\t\t<\/g>\n\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--query\" r=\"5\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-node)\" filter=\"url(#ns-aih-zF2A2rh-1-turing-t-glow)\" data-route=\"#ns-aih-zF2A2rh-1-turing-t-qa\" data-cycle=\"9000\" data-start=\"450\" data-end=\"2200\" data-radius=\"5\" data-static=\".48\"\/>\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--query\" r=\"5\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-node)\" filter=\"url(#ns-aih-zF2A2rh-1-turing-t-glow)\" data-route=\"#ns-aih-zF2A2rh-1-turing-t-qb\" data-cycle=\"9000\" data-start=\"800\" data-end=\"2550\" data-radius=\"5\" data-static=\".58\"\/>\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--reply\" r=\"4.5\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-blue)\" filter=\"url(#ns-aih-zF2A2rh-1-turing-t-glow)\" data-route=\"#ns-aih-zF2A2rh-1-turing-t-qa\" data-cycle=\"9000\" data-start=\"3350\" data-end=\"5150\" data-reverse=\"1\" data-radius=\"4.5\" data-static=\".72\"\/>\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--reply\" r=\"4.5\" fill=\"url(#ns-aih-zF2A2rh-1-turing-t-blue)\" filter=\"url(#ns-aih-zF2A2rh-1-turing-t-glow)\" data-route=\"#ns-aih-zF2A2rh-1-turing-t-qb\" data-cycle=\"9000\" data-start=\"3650\" data-end=\"5450\" data-reverse=\"1\" data-radius=\"4.5\" data-static=\".64\"\/>\n\t\t<\/svg>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">With the appearance of the first computers in the 1940s, the fascination with the technology quickly led to the idea that they could soon perform as intelligently as humans. In 1950, British mathematician and computer scientist Alan Turing devised a test to evaluate when a computer would be able to emulate a human conversation convincingly. It took almost 65 years for the first simulation to narrowly pass.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Eliza<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--eliza\"\n        id=\"ns-aih-zF2A2rh-2-eliza\"\n        data-aihm-scene=\"eliza\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<a class=\"aihm-visual aihm-action-surface aihm-eliza-preview\" href=\"#eliza\" aria-label=\"Open the 1966 Eliza conversation\">\n\t\t<div class=\"aihm-eliza-paper\">\n\t\t\t<div class=\"aihm-eliza-log\" aria-hidden=\"true\"><\/div>\n\t\t\t<span class=\"aihm-eliza-cursor\" aria-hidden=\"true\">\u258c<\/span>\n\t\t<\/div>\n\t\t<span class=\"aihm-hitarea\" aria-hidden=\"true\">\n\t\t\t<span class=\"aihm-button\">Talk to Eliza<\/span>\n\t\t<\/span>\n\t<\/a>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">When German-American computer scientist Joseph Weizenbaum created chat program &quot;Eliza&quot; in 1966, simulating the dialogue with a psychologist, it was meant like a playful first attempt at processing natural speech. Even though the logic behind it was very simple, many people considered it intelligent and expected computers to be able to speak like humans soon.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aih-slide-link-row\"><a class=\"ns-aih-slide-link\" href=\"#eliza\">Talk to Eliza<span class=\"ns-aih-slide-link-arrow\" aria-hidden=\"true\">&rarr;<\/span><\/a><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Machine Learning<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--machinelearning\"\n        id=\"ns-aih-zF2A2rh-3-machinelearning\"\n        data-aihm-scene=\"machinelearning\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-vector-scene aihm-ml-preview\" 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data-route=\"#ns-aih-zF2A2rh-3-machinelearning-ml-h2o1\" data-cycle=\"8200\" data-start=\"2250\" data-end=\"3650\" data-radius=\"4.5\" data-static=\".58\"\/>\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--error\" r=\"5\" fill=\"url(#ns-aih-zF2A2rh-3-machinelearning-ml-error)\" filter=\"url(#ns-aih-zF2A2rh-3-machinelearning-ml-glow)\" data-route=\"#ns-aih-zF2A2rh-3-machinelearning-ml-h2o1\" data-cycle=\"8200\" data-start=\"4100\" data-end=\"5500\" data-reverse=\"1\" data-radius=\"5\" data-static=\".72\"\/>\n\t\t\t<circle class=\"aihm-vector-token aihm-vector-token--error\" r=\"4.5\" fill=\"url(#ns-aih-zF2A2rh-3-machinelearning-ml-error)\" filter=\"url(#ns-aih-zF2A2rh-3-machinelearning-ml-glow)\" data-route=\"#ns-aih-zF2A2rh-3-machinelearning-ml-i2h2\" data-cycle=\"8200\" data-start=\"5300\" data-end=\"6800\" data-reverse=\"1\" data-radius=\"4.5\" data-static=\".63\"\/>\n\t\t<\/svg>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">With increasingly powerful computers and larger storage capabilities that were able to handle large datasets, the first successful machine learning approaches were introduced. They were based on the ability to autonomously find patterns in data, relate them back to certain events and conditions and suggest or take action.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Playing Chess (and Winning)<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--deepblue\"\n        id=\"ns-aih-zF2A2rh-4-deepblue\"\n        data-aihm-scene=\"deepblue\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-deepblue-preview\" role=\"group\" aria-label=\"Deep Blue chess preview\">\n\t\t<div class=\"aihm-db-console\">\n\t\t\t<header class=\"aihm-db-head dbct-header\">\n\t\t\t\t<div class=\"dbct-bars\" aria-hidden=\"true\"><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><i><\/i><\/div>\n\t\t\t\t<div class=\"dbct-title\" role=\"heading\" aria-level=\"3\">DEEP BLUE<small>RS\/6000 SP &nbsp;\u00b7&nbsp; OPERATOR CONSOLE<\/small><\/div>\n\t\t\t\t<div class=\"dbct-hright\">GAME 6 &nbsp;\u00b7&nbsp; NEW YORK 1997<br>ENGINE: <b>DEEP BLUE<\/b><\/div>\n\t\t\t<\/header>\n\t\t\t<div class=\"aihm-db-layout\">\n\t\t\t\t<div class=\"aihm-db-board\" role=\"img\" aria-label=\"Chess board replaying the opening of game six\"><\/div>\n\t\t\t\t<div class=\"aihm-db-telemetry\">\n\t\t\t\t\t<div>MOVE <b class=\"aihm-db-move\">1. e4<\/b><\/div>\n\t\t\t\t\t<div>PLY <b class=\"aihm-db-search\">1 \/ 10<\/b><\/div>\n\t\t\t\t\t<div>RESULT <b>DEEP BLUE 1\u20130<\/b><\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t<div class=\"aihm-db-controls dbct-controls\">\n\t\t\t\t<button type=\"button\" data-dbct-popup-trigger=\"deepblue\" aria-label=\"Open the Deep Blue chess experience\">Play Chess<\/button>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">In 1997, IBM&#039;s Deep Blue supercomputer won its first match against acting chess champion Garry Kasparov. While mostly driven by sheer power which helped build its game on computing more than 200 million positions a second, it was using machine learning elements (heuristics and minimax optimization techniques) mid-game, which can be considered AI.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aih-slide-link-row\"><a class=\"ns-aih-slide-link\" href=\"#deepblue\">Play Chess<span class=\"ns-aih-slide-link-arrow\" aria-hidden=\"true\">&rarr;<\/span><\/a><\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Seeing and Knowing<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--vision\"\n        id=\"ns-aih-zF2A2rh-5-vision\"\n        data-aihm-scene=\"vision\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-vision-real\" role=\"img\" aria-label=\"Animated computer-vision analysis of a cherry image: real image, inverted scan, pixelated scan, then the label cherry with contour overlays\">\n\t\t<div class=\"aihm-vision-photo aihm-vision-photo--clear\" style=\"background-image:url(https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/vision-cherry-clear-v046.webp)\"><\/div>\n\t\t<div class=\"aihm-vision-layer aihm-vision-layer--invert\">\n\t\t\t<div class=\"aihm-vision-photo aihm-vision-photo--invert\" style=\"background-image:url(https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/vision-cherry-invert-v046.webp)\"><\/div>\n\t\t<\/div>\n\t\t<div class=\"aihm-vision-layer aihm-vision-layer--pixel\">\n\t\t\t<div class=\"aihm-vision-photo aihm-vision-photo--pixel\" style=\"background-image:url(https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/vision-cherry-pixel-v046.webp)\"><\/div>\n\t\t<\/div>\n\t\t<div class=\"aihm-vision-layer aihm-vision-layer--final\">\n\t\t\t<div class=\"aihm-vision-photo aihm-vision-photo--final\" style=\"background-image:url(https:\/\/www.9senses.ai\/wp-content\/plugins\/ninesenses-ai-history\/assets\/images\/vision-cherry-final-v072.webp)\"><\/div>\n\t\t\t<div class=\"aihm-vision-tag-wrap\" aria-hidden=\"true\">\n\t\t\t\t<div class=\"aihm-vision-tag-box\">cherry<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t\t<div class=\"aihm-vision-grid\" aria-hidden=\"true\"><\/div>\n\t\t<div class=\"aihm-vision-scanline aihm-vision-scanline--invert\" aria-hidden=\"true\"><\/div>\n\t\t<div class=\"aihm-vision-scanline aihm-vision-scanline--pixel\" aria-hidden=\"true\"><\/div>\n\t\t<div class=\"aihm-vision-scanline aihm-vision-scanline--final\" aria-hidden=\"true\"><\/div>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">While optical character recognition (OCR) had been developed long ago, computers became capable of &quot;seeing&quot; in the late 20th and the early 21st century. This is when the first face and object recognition systems were developed. By now, AI is able to routinely identify people and objects and also understand what they are doing.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Solving Complex Problems<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--deeplearning\"\n        id=\"ns-aih-zF2A2rh-6-deeplearning\"\n        data-aihm-scene=\"deeplearning\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-dl-preview\" role=\"img\" aria-label=\"Animated deep-learning process adapted from the 9Senses machine-learning explainer: data becomes vectors, trains a model, produces output, is checked and feeds back\">\n\t\t<canvas class=\"aihm-dl-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t<div class=\"aihm-dl-node aihm-dl-node--data\" data-dl-step=\"0\">data<\/div>\n\t\t<div class=\"aihm-dl-node aihm-dl-node--vectors\" data-dl-step=\"1\">vectors<\/div>\n\t\t<div class=\"aihm-dl-core\" data-dl-step=\"2\">model<\/div>\n\t\t<div class=\"aihm-dl-node aihm-dl-node--output\" data-dl-step=\"3\">output<\/div>\n\t\t<div class=\"aihm-dl-node aihm-dl-node--check\" data-dl-step=\"4\">check<\/div>\n\t\t<div class=\"aihm-dl-node aihm-dl-node--feedback\" data-dl-step=\"5\">feedback<\/div>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">The previous decade was the era where all previous efforts in making computers act &quot;intelligently&quot; came together, and where many breakthroughs shifted public attention towards the term &quot;Artificial Intelligence&quot; again, after it had been rarely used since the 1970s. By 2010, normal desktop and laptop computers were strong enough to perform AI tasks.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<section class=\"ns-aih-slide\" data-index=\"7\" aria-hidden=\"true\">\n\t\t\t\t\t\t<h3 class=\"ns-aih-slide-title\">Listening and Speaking<\/h3>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-scene\">\n\t\t\t\t\t\t\t    <section\n        class=\"aihm-scene aihm-scene--language\"\n        id=\"ns-aih-zF2A2rh-7-language\"\n        data-aihm-scene=\"language\"\n        data-autoplay=\"1\"\n        style=\"--aihm-height:260px\"\n    >\n        <div class=\"aihm-frame\">\n            \t<div class=\"aihm-visual aihm-nlp-preview\" role=\"img\" aria-label=\"Animated natural-language-processing diagram adapted from the 9Senses NLP explainer: input becomes tokens, vectors and context, then output is checked\">\n\t\t<canvas class=\"aihm-nlp-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t<div class=\"aihm-nlp-tokenline\" aria-hidden=\"true\">\n\t\t\t<span>Can<\/span><span>we<\/span><span>ship<\/span><span>?<\/span>\n\t\t<\/div>\n\t\t<div class=\"aihm-nlp-node aihm-nlp-node--input\" data-nlp-step=\"0\">input<\/div>\n\t\t<div class=\"aihm-nlp-node aihm-nlp-node--tokens\" data-nlp-step=\"1\">tokens<\/div>\n\t\t<div class=\"aihm-nlp-node aihm-nlp-node--vectors\" data-nlp-step=\"2\">vectors<\/div>\n\t\t<div class=\"aihm-nlp-core\" data-nlp-step=\"3\">context<\/div>\n\t\t<div class=\"aihm-nlp-node aihm-nlp-node--output\" data-nlp-step=\"4\">output<\/div>\n\t\t<div class=\"aihm-nlp-node aihm-nlp-node--check\" data-nlp-step=\"5\">check<\/div>\n\t\t<div class=\"aihm-nlp-outputline\" aria-hidden=\"true\"><span>yes<\/span><span>\u2014<\/span><span>with<\/span><span>review<\/span><\/div>\n\t\t<div class=\"aihm-nlp-warning\" data-nlp-step=\"5\" aria-hidden=\"true\">confidence <b>\u2260<\/b> correctness<\/div>\n\t<\/div>\n\t        <\/div>\n    <\/section>\n    \t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<div class=\"ns-aih-slide-text\">\n\t\t\t\t\t\t\t<p class=\"ns-aih-slide-body\">Finally, conversational AI is able to have conversations with humans based on Large Language Models that have been released. Those models are routinely able to pass the Turing Test, which means that they are able to understand and communicate back in natural language.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t<\/div>\n\t<\/div>\n\t<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_3 et_pb_section et_section_regular et_block_section\">\n<div class=\"et_pb_row_5 et_pb_row et_flex_row ns-cta\">\n<div class=\"et_pb_column_6 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_4 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><p>But what is AI really? We have asked two conversational AI systems about their definition of Artificial Intelligence and they came back with quite divergent answers. <a href=\"#AIonAI\">Click to see what AI has to say on AI<\/a><\/p>\n<\/div><\/div>\n\n<div class=\"et_pb_text_5 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><p>With two differing statements from two AI systems, we are not afraid of creating our own answer. We at 9senses define AI as<strong> \"a computer system that is able to react to an event it has never experienced before in a meaningful way that is adequate to that event, based on the analysis of many similar events from data.\"<\/strong> This ability clearly distinguishes it from traditional computer logic where each event (or combination of events) has only one defined reaction. We explicitly stay away from comparing it with humans, because in some areas, computers <a href=\"\/why-9\">are still eons away from reaching our abilities, while in others, they massively outperform us<\/a>.<\/p>\n<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_7 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_module et_pb_button_module_wrapper et_pb_button_0_wrapper\"><a class=\"et_pb_button_0 et_pb_button et_pb_bg_layout_light et_pb_module et_block_module\" href=\"#AIonAI\" style=\"text-wrap:balance\">what AI says about AI<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_4 et_pb_section et_section_regular et_block_section ns-block ns-tabset\" id=\"Key_fields_of_AI\" lang=\"en\">\n<div class=\"et_pb_row_6 et_pb_row et_block_row\">\n<div class=\"et_pb_column_8 et_pb_column et_pb_column_4_4 et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough\">\n<div class=\"et_pb_text_6 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><h2 style=\"display: inline; margin: 0 0.6em 0 0; padding: 0;\">Key Fields of AI<\/h2>\n<p><span>There are various key AI technology areas, here is one of many ways to break them down:<\/span><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_7 et_pb_row et_flex_row\">\n<div class=\"et_pb_column_9 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide hovergroup preset--module--divi-column--47yw920uxm\" id=\"trigger-ml\">\n<div class=\"et_pb_blurb_0 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module\"><div class=\"et_pb_blurb_content et_flex_module\"><div class=\"et_pb_blurb_container\"><h3 class=\"et_pb_module_header\">Ma\u00adchine Learn\u00ading<\/h3><div class=\"et_pb_blurb_description\"><p><span>Finding patterns in large datasets and drawing con\u00ad\u00ad\u00adclusions is at the core of most AI applications these days.\u00a0 Machine Lear\u00adn\u00ading provides the statistical methods to make it happen.<\/span><\/p>\n<\/div><\/div><\/div><\/div>\n\n<div class=\"et_pb_icon_0 et_pb_icon et_pb_module et_flex_module\"><span class=\"et_pb_icon_wrap\"><span class=\"et-pb-icon\">3<\/span><\/span><\/div>\n<\/div>\n\n<div class=\"et_pb_column_10 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide hovergroup preset--module--divi-column--47yw920uxm\" id=\"trigger-nlp\">\n<div class=\"et_pb_blurb_1 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module\"><div class=\"et_pb_blurb_content et_flex_module\"><div class=\"et_pb_blurb_container\"><h3 class=\"et_pb_module_header\">Nat\u00adural Lan\u00adguage Pro\u00adcess\u00ading<\/h3><div class=\"et_pb_blurb_description\"><p>Being able to communicate with humans is one of the most recent key AI develop\u00adments that helps interact with computers, for example in customer-facing IT.<\/p>\n<\/div><\/div><\/div><\/div>\n\n<div class=\"et_pb_icon_1 et_pb_icon et_pb_module et_flex_module\"><span class=\"et_pb_icon_wrap\"><span class=\"et-pb-icon\">3<\/span><\/span><\/div>\n<\/div>\n\n<div class=\"et_pb_column_11 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide hovergroup preset--module--divi-column--47yw920uxm\" id=\"trigger-cv\">\n<div class=\"et_pb_blurb_2 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module\"><div class=\"et_pb_blurb_content et_flex_module\"><div class=\"et_pb_blurb_container\"><h3 class=\"et_pb_module_header\">Com\u00adputer Vi\u00adsion<\/h3><div class=\"et_pb_blurb_description\"><p>Finding items and differences in still or moving imagery is something that computers excel at, for example when it comes to surveillance, irre\u00adgularity detection or simply - counting.<\/p>\n<\/div><\/div><\/div><\/div>\n\n<div class=\"et_pb_icon_2 et_pb_icon et_pb_module et_flex_module\"><span class=\"et_pb_icon_wrap\"><span class=\"et-pb-icon\">3<\/span><\/span><\/div>\n<\/div>\n\n<div class=\"et_pb_column_12 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide hovergroup preset--module--divi-column--47yw920uxm\" id=\"trigger-robotics\">\n<div class=\"et_pb_blurb_3 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module\"><div class=\"et_pb_blurb_content et_flex_module\"><div class=\"et_pb_blurb_container\"><h3 class=\"et_pb_module_header\">Ro\u00adbot\u00adics<\/h3><div class=\"et_pb_blurb_description\"><p>Creating autonomous sys\u00adtems that perform phy\u00adsical actions, like driving a vehicle based on controlling equipment using sensor in\u00adput and logic, is a key field of AI, albeit a difficult one.<\/p>\n<\/div><\/div><\/div><\/div>\n\n<div class=\"et_pb_icon_3 et_pb_icon et_pb_module et_flex_module\"><span class=\"et_pb_icon_wrap\"><span class=\"et-pb-icon\">3<\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_5 et_pb_section et_section_regular et_flex_section ns-panel\" id=\"ml\" style=\"--ns-rail-w:264px; --ns-body-color:#D3D3D3;\">\n<div class=\"et_pb_row_8 et_pb_row et_flex_row\">\n<div class=\"et_pb_column_13 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_7 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><p>Whichever AI field you look at, whether NLP, Computer Vision or Robotics, it is usually Machine Learning doing the actual work underneath: models learn from historical data and apply what they have learned to data they have never seen before. Or, as Wikipedia puts it: \"Machine Learning is a field of study in artificial intelligence concerned with the development of statistical algorithms that can learn from data and generalize to unseen data; and thus perform tasks without explicit instructions.\"<\/p>\n<\/div><\/div>\n\n<div class=\"et_pb_code_2 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\">\t<div\n\t\tid=\"ns-aix-1\"\n\t\tclass=\"ns-aix ns-aix-ml\"\n\t\tdata-topic=\"ml\"\n\t\tdata-flow=\"core\"\n\t\t\t\tdata-step=\"0\"\n\t\tdata-interval=\"9000\"\n\t\t\t\tdata-autoplay=\"1\"\n\t\trole=\"region\"\n\t\taria-label=\"So funktioniert maschinelles Lernen\"\n\t\tstyle=\"--ns-aix-accent:#58a7f9;--ns-aix-secondary:#2b6cb0\"\n\t>\n\t\t<header class=\"ns-aix-head\">\n\t\t\t\t\t\t<h3 class=\"ns-aix-title\">So funktioniert maschinelles Lernen<\/h3>\n\t\t\t<p class=\"ns-aix-intro\">Maschinelles Lernen ist kein starrer Ablauf logischer Routinen. Es ist ein System, das in Beispielen n\u00fctzliche Muster findet, diese Muster in ein Modell \u00fcberf\u00fchrt und das Modell auf neue Situationen anwendet.<\/p>\n\t\t\t\t\t\t\t\t<\/header>\n\n\t\t<div class=\"ns-aix-body\">\n\t\t\t<div class=\"ns-aix-copy\">\n\t\t\t\t<div class=\"ns-aix-progress\" aria-hidden=\"true\"><span><\/span><\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-1-flow-panel-core\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel ns-on\"\n\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps ns-on\" data-flow=\"core\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step ns-on\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"observe\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Beobachten<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Rohe F\u00e4lle gelangen ins System.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"encode\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Kodieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Bedeutung wird zu Geometrie.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"train\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Trainieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Vorhersagen, Fehler messen, nachjustieren.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"generalize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verallgemeinern<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Struktur statt Auswendiglernen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"infer\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Anwenden<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Neue Eingabe wird zur Entscheidungshilfe.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"validate\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Validieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Das Modell muss au\u00dferhalb des Trainings gepr\u00fcft werden.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"improve\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verbessern<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">R\u00fcckmeldung macht aus dem Betrieb Lernen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t<div class=\"ns-aix-stage\" aria-label=\"Animiertes Vektorkarten-Prozessdiagramm\">\n\t\t\t\t<canvas class=\"ns-aix-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-on\" data-flow=\"core\" data-step=\"0\" data-key=\"observe\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>daten<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"1\" data-key=\"encode\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>vektoren<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"2\" data-key=\"train\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>modell<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"3\" data-key=\"generalize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>struktur<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"4\" data-key=\"infer\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>ausgabe<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"5\" data-key=\"validate\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pr\u00fcfen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"6\" data-key=\"improve\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>r\u00fcckmeldung<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t<\/div>\n\n\t\t<div class=\"ns-aix-controls\">\n\t\t\t<div class=\"ns-aix-dots\" role=\"navigation\" aria-label=\"Schrittnavigation\">\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset ns-on\"\n\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr So funktioniert maschinelles Lernen\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot ns-on\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Beobachten\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Kodieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Trainieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Verallgemeinern\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Anwenden\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Validieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Verbessern\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-1-panel-core-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\n\t\t<div class=\"ns-aix-below\" aria-live=\"polite\">\n\t\t\t<div class=\"ns-aix-explain\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Mit Beispielen beginnen<\/h4>\n\t\t\t\t\t\t\t<p>Maschinelles Lernen beginnt mit Beispielen: Dokumenten, F\u00e4llen, Sensorwerten, Kundengespr\u00e4chen oder Gesch\u00e4ftsereignissen. Entscheidend ist nicht die Menge allein, sondern ob die Daten die Entscheidungen abbilden, die das Modell sp\u00e4ter st\u00fctzen soll \u2013 und ob sie den Aufwand f\u00fcr Erhebung und Bereinigung wert sind.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>Signale in Vektoren \u00fcberf\u00fchren<\/h4>\n\t\t\t\t\t\t\t<p>Texte, Bilder und Zahlen werden in numerische Merkmale oder Vektoren \u00fcberf\u00fchrt: Koordinaten, die n\u00fctzliche Muster wie \u00c4hnlichkeit, H\u00e4ufigkeit, Absicht, Kontext oder Risiko bewahren. Deshalb kann ein Modell Dinge vergleichen, die nicht w\u00f6rtlich identisch sind.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Das Modell anpassen<\/h4>\n\t\t\t\t\t\t\t<p>Das Modell trifft eine Vorhersage, vergleicht sie mit der erwarteten Antwort, misst den Fehler und passt interne Gewichte an. Manche Modelle lernen so aus beschrifteten Beispielen; andere finden Struktur ohne Beschriftung, und gro\u00dfe Sprachmodelle bringen es sich weitgehend selbst aus rohem Text bei. Die Wiederholung macht aus einzelnen Beispielen ein wiederverwendbares Muster.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Struktur lernen, nicht eine Liste<\/h4>\n\t\t\t\t\t\t\t<p>Ein brauchbares Modell lernt seine Trainingsf\u00e4lle nicht einfach auswendig \u2013 dieses Fehlverhalten hei\u00dft Overfitting. Es erfasst genug Struktur, um bei neuen F\u00e4llen gut zu arbeiten, die inhaltlich \u00e4hnlich sind, auch wenn Wortlaut, Format oder Kontext nicht identisch sind.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Das trainierte Modell anwenden<\/h4>\n\t\t\t\t\t\t\t<p>Bei der Inferenz durchl\u00e4uft neue Eingabe das trainierte Modell. Die Ausgabe kann ein Score, eine Klassifikation, eine Empfehlung, eine Prognose, eine erzeugte Antwort oder eine sortierte Dokumentenliste sein.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Qualit\u00e4t und Risiko steuern<\/h4>\n\t\t\t\t\t\t\t<p>Separate Testdaten, menschliche Pr\u00fcfung und Monitoring decken schwache Randf\u00e4lle, Verzerrungen, Halluzinationen, Drift und Compliance-Risiken auf, bevor die Automatisierung Kundschaft, Belegschaft oder regulierte Entscheidungen ber\u00fchrt.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-1-panel-core-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Den R\u00fcckkopplungskreis schlie\u00dfen<\/h4>\n\t\t\t\t\t\t\t<p>Tats\u00e4chliche Ergebnisse und Korrekturen flie\u00dfen ins System zur\u00fcck. Unachtsam gehandhabt kann das alte Verzerrungen verfestigen; deshalb werden Modell, Retrieval-Schicht, Prompts, Datenpipeline und Governance-Regeln bewusst verbessert, statt sie treiben zu lassen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"ns-aix-aspects\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset ns-on\" data-flow=\"core\" data-step=\"0\" aria-hidden=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>\u00dcberwachtes Lernen arbeitet mit beschrifteten Beispielen; un\u00fcberwachtes Lernen findet Struktur in unbeschrifteten Daten; best\u00e4rkendes Lernen verbessert sich durch Versuch und Irrtum mittels R\u00fcckmeldung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Um Maschinenausf\u00e4lle vorherzusagen, werden Betriebsdaten mit erfassten Ausf\u00e4llen verkn\u00fcpft, damit das System Beispiele zum Lernen hat.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Maschinelles Lernen ist in erster Linie Mustererkennung in gro\u00dfen Datenbest\u00e4nden. Erst die Kodierung macht diese Muster messbar.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Vektordarstellungen erlauben Such-, Empfehlungs- und Retrieval-Systemen, Dinge zu vergleichen, die inhaltlich \u00e4hnlich statt formal identisch sind.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Hintergrund<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Maschinelles Lernen geht auf die 1950er-Jahre zur\u00fcck, als Forschende Algorithmen bauten, die einfache Muster in Daten erkennen konnten. Gro\u00dfe Datenmengen, leistungsf\u00e4hige Hardware \u2013 insbesondere GPUs \u2013 und verbesserte Algorithmen trieben die Durchbr\u00fcche des fr\u00fchen 21. Jahrhunderts.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>W\u00e4hrend des Trainings trifft der Algorithmus Vorhersagen und vergleicht sie mit bekannten Ergebnissen. Vielfach wiederholt verbessert das die Genauigkeit schrittweise.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Modernes maschinelles Lernen st\u00fctzt sich oft auf k\u00fcnstliche neuronale Netze \u2013 mathematische Systeme, lose vom Gehirn inspiriert, die sich durch Erfahrung verbessern.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das fertige Modell muss mit neuen, ungesehenen Daten derselben Art funktionieren und nicht nur die F\u00e4lle wiedergeben, mit denen es trainiert wurde.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was maschinelles Lernen leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Maschinelles Lernen treibt Suchmaschinen, Empfehlungssysteme, Sprachassistenten, Betrugserkennung, Bildanalyse und autonome Systeme an \u2013 in vielen eng umrissenen Aufgaben schneller und genauer als Menschen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Es kann Tumore in Aufnahmen erkennen, Anlagenausf\u00e4lle vorhersagen, Sprachen \u00fcbersetzen sowie Texte, Bilder und Code erzeugen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Weil ein Modell Kontext nicht auf abstrakter Ebene versteht, braucht es klare F\u00fchrung bei Training und Pr\u00fcfung, mit Grenzen, die Menschen setzen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein intransparentes Modell kann zur Blackbox werden, bei der unklar bleibt, welche Muster seine Entscheidungen bestimmen. Wo die Auswirkungen gro\u00df sind, ist sorgf\u00e4ltige Governance unerl\u00e4sslich.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was maschinelles Lernen leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Maschinelles Lernen ist dort am st\u00e4rksten, wo gro\u00dfe Mengen strukturierter oder unstrukturierter Daten Muster verbergen, die f\u00fcr manuelle Analyse zu fein sind: Wirkstoffforschung und Klimamodellierung in der Wissenschaft; Prognose, Segmentierung und Prozessoptimierung im Unternehmen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ergebnisse h\u00e4ngen stark von der Datenqualit\u00e4t ab \u2013 schlechte Daten f\u00fchren zu falschen Ergebnissen, und ungesteuerte R\u00fcckkopplungen verst\u00e4rken unbemerkt die Verzerrungen von gestern.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_14 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_8 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><h3>The Challenges<\/h3>\n<p>Machine Learning has important limitations. It heavily depends on the quality and quantity of the underlying data to find the relevant statistical patterns. Bad data leads to incorrect outcomes.<\/p>\n<p>As machine learning - like all \"AI\" - doesn't really understand the context on an abstract level, it needs clear guidance during training and reviews, often coupled with additional boundaries set by humans.<\/p>\n<p>This becomes particularly difficult when the model itself is intransparent and becomes a \"black box\", where it remains unclear what patterns drive decisions made by ML. Thus, careful governance is essential, particularly in areas with high impact.<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_9 et_pb_row et_flex_row\" style=\"--ns-caro-top:26px\">\n<div class=\"et_pb_column_15 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_code_3 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\"><div class=\"nsp-frame nsp-frame--transparent\"><div class=\"nsp-frame-head\"><h2>Featured Projects<\/h2><\/div><div class=\"nsp-carousel-wrap\" data-base-width=\"240\" data-loop=\"1\"><button type=\"button\" class=\"nsp-nav nsp-prev\" aria-label=\"Previous\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x34;<\/span><\/button><div class=\"nsp-carousel\">\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"12\" aria-label=\"Intelligent Data Retrieval Agent\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Intelligent Data Retrieval Agent<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Production-ready AI retrieval system using LLMs and semantic search to transform fragmented data into reliable, searchable knowledge.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"13\" aria-label=\"Visual Search Recommendations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-socks\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Search Recommendations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">eCommmerce plugin that enables searching for visually similar products, helping customers to find and compare multiple related items.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"14\" aria-label=\"Visual Assistance for Seniors\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-glasses\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Assistance for Seniors<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Visual Assistance App: enabling visual assistance for seniors by helping position determination using Computer Vision and Deep Learning.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"1\" aria-label=\"Electrical Switch Monitor\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-toggle-on\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Electrical Switch Monitor<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Public transportation: using AI-driven vision to monitor old-fashioned electrical relays and also to evaluate potential failures for predictive maintenance.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"5\" aria-label=\"Hydropower Plant Operations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Hydropower Plant Operations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Create a control and monitoring solution for all plant operations, including predictive maintenance logic and intrusion mon\u00aditoring.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"2\" aria-label=\"Customer Interaction Analysis\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Customer Interaction Analysis<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">SaaS project platform: the objective was to evaluate dialogue quality using an AI model to ensure timely intervention and customer care.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"6\" aria-label=\"Motion-sensitive wearables\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-shirt\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Motion-sensitive wearables<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Wearable fabric-based devices with embedded microcontrollers and sensitivity for motion, heartbeat, body temperature and sweat detection.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t<\/div><button type=\"button\" class=\"nsp-nav nsp-next\" aria-label=\"Next\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x35;<\/span><\/button><\/div><script>(function(){\n\t\t\tif (!window.nspComputeLayout) {\n\t\t\t\twindow.NSP_BASE_CARD_WIDTH = 240;\n\t\t\t\twindow.nspIsFluidWidth = function(){ return window.innerWidth > 640; };\n\t\t\t\twindow.nspComputeLayout = function(available, gap, totalCards, baseWidth){\n\t\t\t\t\tvar BASE = baseWidth || window.NSP_BASE_CARD_WIDTH;\n\t\t\t\t\tavailable = Math.max(0, available || 0);\n\t\t\t\t\tgap = Math.max(0, gap || 0);\n\t\t\t\t\ttotalCards = Math.max(0, totalCards || 0);\n\t\t\t\t\tif (!totalCards){\n\t\t\t\t\t\treturn { count: 0, width: BASE, center: true };\n\t\t\t\t\t}\n\t\t\t\t\tvar per = BASE + gap;\n\t\t\t\t\tvar baseCount = Math.max(1, Math.floor((available + gap) \/ per));\n\t\t\t\t\tvar used = baseCount * BASE + (baseCount - 1) * gap;\n\t\t\t\t\tvar remainder = available - used;\n\t\t\t\t\t\/\/ Only create an extra visible slot when there is actually another card to fill it.\n\t\t\t\t\t\/\/ If exactly the base-width row count is present, distribute those cards evenly\n\t\t\t\t\t\/\/ across the row instead of leaving them beside a phantom extra slot.\n\t\t\t\t\tvar fullCount = (totalCards > baseCount && remainder >= (2 \/ 3) * BASE) ? baseCount + 1 : baseCount;\n\t\t\t\t\tfullCount = Math.max(1, fullCount);\n\t\t\t\t\tvar fullWidth = (available - (fullCount - 1) * gap) \/ fullCount;\n\t\t\t\t\tif (!isFinite(fullWidth) || fullWidth <= 0){ fullWidth = BASE; }\n\n\t\t\t\t\t\/\/ One or two cards should never grow just because the row is wide.\n\t\t\t\t\t\/\/ They keep the base width, sit at the left, and leave the rest of the row empty.\n\t\t\t\t\tif (totalCards < 3){\n\t\t\t\t\t\tvar smallMax = (available - (totalCards - 1) * gap) \/ totalCards;\n\t\t\t\t\t\tvar smallWidth = (isFinite(smallMax) && smallMax > 0) ? 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Published\n\t\t\t\t\/\/ as a custom property the stylesheet reads.\n\t\t\t\twindow.nspTrackPadX = function(track){\n\t\t\t\t\tvar cs = window.getComputedStyle(track);\n\t\t\t\t\treturn (parseFloat(cs.paddingLeft) || 0) + (parseFloat(cs.paddingRight) || 0);\n\t\t\t\t};\n\t\t\t\twindow.nspSyncNav = function(wrap){\n\t\t\t\t\t\/\/ People cards anchor on the photo, which is the visual mass of\n\t\t\t\t\t\/\/ the card. Project cards have no photo -- only a small icon\n\t\t\t\t\t\/\/ at the top -- so they anchor on the card panel itself and\n\t\t\t\t\t\/\/ the arrows land on its vertical centre. 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The solution transformed scattered legacy records into structured, searchable knowledge, enabling users to retrieve relevant information within seconds instead of manually searching across hundreds of documents.<\/p>\n<p>The project combined retrieval-augmented generation (RAG), vector search, and modern LLM technologies to deliver reliable, context-aware information retrieval. Designed with a modular architecture, the system supports scalability, maintainability, and future extensions while ensuring robust retrieval quality across heterogeneous data sources.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>AI Engineer<\/p>\n<p>Python \u2022 LangChain \u2022 OpenAI \u2022 Qdrant \u2022 Semantic Search \u2022 RAG \u2022 Streamlit<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"13\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Search Recommendations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For VisualSearch, the focus was on developing and deploying e-commerce plugins to enhance recommendation functionalities in web shops. The plugins were successfully launched in the store and happily adopted by customers, demonstrating their practical use in improving e-commerce experiences. Key elements included:<br \/>\n- computation of visual embeddings from appearances of e-commerce products<br \/>\n- building and maintaining a search index using these embeddings<br \/>\n- providing a cloud-based API for Shopware and Prestashop plugins<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"369\" height=\"455\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png 369w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-10x12.png 10w\" sizes=\"(max-width: 369px) 100vw, 369px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, leveraging AWS services, Python, and deep learning frameworks like Keras. The project integrated cloud-based solutions using CloudFormation, Lambda, and Gateway for scalable and efficient deployment, using SQL and DynamoDB for data management.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"14\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Assistance for Seniors<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For the Austrian Institute of Technology (as a part of the national research project LARAH), a prototype of an assistance system for visual indoor localization for disabled and elderly persons was developed. By leveraging Computer Vision and Deep Learning, innovative algorithms for position determination were implemented. The project resulted in a functional prototype, including two Android applications for real-time localization. Key elements included:<br \/>\n- visual recognition of persons using Deep-Learning models<br \/>\n- visual reconstruction and localization of indoor environments using Structure-from-Motion and Machine Learning algorithms<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"366\" height=\"451\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png 366w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-10x12.png 10w\" sizes=\"(max-width: 366px) 100vw, 366px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, developed under Python using Deep Learning models like TensorFlow, custom-developed Structure-from-Motion software and custom camera calibration software. Additionally, as a part of the project, two Android apps were modified and integrated together onto the Robot Operating System on the mobile platform.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"1\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Electrical Switch Monitor<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a public transportation network, the objective was to optimize the monitoring of their legacy electrical switchboards. These decade-old items that are often located in very remote areas are prone to failures and tracking of errors was not possible. The objective was to enable real-time tracking and the recognition of upcoming failures from changed switching behavior. The key elements were:<\/p>\n<ul>\n<li>Development of specific hardware configuration with custom housings (3D printed) to mount instead of regular switchboard covers;<\/li>\n<li>Camera control and initial image generation on Raspberry Pi integrated in housing;<\/li>\n<li>Initial scan of switch layout and labels;<\/li>\n<li>Identification of switching operations and registration of new positions;<\/li>\n<li>Identification of irregular switching patterns (delays, other irregularities) to indicate upcoming failures for predictive maintenance;<\/li>\n<li>Update of central database and cloud solution with last state and observed switching patterns;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"959\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-1024x959.jpg\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-980x918.jpg 980w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-480x450.jpg 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1024px, 100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>The solution was implemented using Python on Raspberry Pi devices, backbone and cloud processing were done using a LAMP stack, with PyTorch, TensorFlow and OpenCV.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"5\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">Hydropower Plant Operations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><div class=\"et_pb_column_11 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_6_24 et_flex_column_12_24_tablet et_flex_column_24_24_phone et_flex_column_12_24_tabletWide preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_2 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module hovergroup preset--group--divi-blurb--divi-box-shadow--default preset--group--divi-blurb--divi-font-body--h19rs5u--7p5s44libg preset--group--divi-blurb--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_content et_flex_module\">\n<div class=\"et_pb_blurb_container\">\n<div class=\"et_pb_blurb_description\">\n<p>Create an integrated monitoring and surveillance solution for small-scale hydropower plants in remote locations. The solution included a full range of required settings:<\/p>\n<ul>\n<li>real-time monitoring and logging of operations<\/li>\n<li>failure detection and automated<\/li>\n<li>predictive maintenance logic to identify early failure<\/li>\n<li>camera-based intrusion and irregularity detection<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was a hybrid solution using Siemens PLCs, combined with small edge computing elements (Raspberry Pi and Arduino). All primary logic (particularly shutdown and load adjustment) was local, but key decisions and aggregations were executed online based on regular data transmission to a cloud-based management and operations suite.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"2\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Customer Interaction Analysis<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a project management SaaS solution where customers were matched with freelancers, a custom AI solution was established with the purpose to improve experiences for all parties. Key purposes were to create an early warning system to help customer service intervene in case of issues:<\/p>\n<ul>\n<li>Identification of unusual patterns (delays indicating inaction, intense exchanges);<\/li>\n<li>Flagging of language transgressions on both sides (use of inappropriate language, aggression);<\/li>\n<li>Matching of final ratings with evaluation of flow and dialogue quality to foster a more honest rating culture;<\/li>\n<li>Language style matching to improve future matching of freelancers to clients;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was implemented using Python on a LAMP stack, with self-developed machine learning libraries.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"6\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-shirt\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">Motion-sensitive wearables<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Arduino-based, with edge ml functionality and periodic link via BLE to connected phone. Machine learning algorithms on cloud detecting various health states and delivering alerts to phone or web app. All logic woven into a cotton fabric wristband.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><\/div><div class=\"nsp-overlay\" id=\"nsp-overlay\" role=\"dialog\" aria-modal=\"true\"><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_6 et_pb_section et_section_regular et_flex_section ns-panel\" id=\"nlp\" style=\"--ns-rail-w:264px; --ns-body-color:#D3D3D3;\">\n<div class=\"et_pb_row_10 et_pb_row et_flex_row\">\n<div class=\"et_pb_column_16 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_9 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><p>There is nothing more fascinating than being able to converse with computers in normal language: asking questions and receiving meaningful answers. Expected for more than half a century, this only became realistically possible a few years ago with the arrival of the first large language models. These LLMs, like ChatGPT or Gemini, have since moved from research milestone to everyday business tool, from employee support to <a href=\"https:\/\/www.9senses.ai\/customer-interaction\/\">customer interactions<\/a>.<\/p>\n<\/div><\/div>\n\n<div class=\"et_pb_code_4 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\">\t<div\n\t\tid=\"ns-aix-2\"\n\t\tclass=\"ns-aix ns-aix-nlp\"\n\t\tdata-topic=\"nlp\"\n\t\tdata-flow=\"development\"\n\t\t\t\tdata-step=\"0\"\n\t\tdata-interval=\"9500\"\n\t\tdata-handoff-duration=\"7200\"\t\tdata-autoplay=\"1\"\n\t\trole=\"region\"\n\t\taria-label=\"So funktioniert NLP\"\n\t\tstyle=\"--ns-aix-accent:#58a7f9;--ns-aix-secondary:#2b6cb0\"\n\t>\n\t\t<header class=\"ns-aix-head\">\n\t\t\t\t\t\t<h3 class=\"ns-aix-title\">So funktioniert NLP<\/h3>\n\t\t\t<p class=\"ns-aix-intro\">Sprachverarbeitung verwandelt Text in Tokens, Vektoren und Wahrscheinlichkeiten. Ein Modell wird einmal durch Training aufgebaut und f\u00fchrt diesen Mechanismus dann bei jeder Anfrage live aus. Dieselbe Mechanik macht es n\u00fctzlich und erkl\u00e4rt, warum Sprachl\u00fccken und Fehler bestehen bleiben.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-flowgroup\">\n\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-tabs\" role=\"tablist\" aria-label=\"So funktioniert NLP\">\n\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\tid=\"ns-aix-2-tab-development\"\n\t\t\t\t\t\t\tclass=\"ns-aix-tab ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"true\"\n\t\t\t\t\t\t\taria-label=\"Entwicklungs- und Trainingspfad von NLP anzeigen\"\n\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\taria-controls=\"ns-aix-2-flow-panel-development\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\tEntwicklung &amp; Grundtraining\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\tid=\"ns-aix-2-tab-execution\"\n\t\t\t\t\t\t\tclass=\"ns-aix-tab\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"Umsetzungspfad von NLP anzeigen\"\n\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\taria-controls=\"ns-aix-2-flow-panel-execution\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\tUmsetzung\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/header>\n\n\t\t<div class=\"ns-aix-body\">\n\t\t\t<div class=\"ns-aix-copy\">\n\t\t\t\t<div class=\"ns-aix-progress\" aria-hidden=\"true\"><span><\/span><\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-2-flow-panel-development\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel ns-on\"\n\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\trole=\"tabpanel\" aria-labelledby=\"ns-aix-2-tab-development\"\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps ns-on\" data-flow=\"development\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step ns-on\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"collect\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Sammeln<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Der Datenbestand setzt die Ausgangslage.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"split\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Token-Regeln<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Tokenisierung ist nicht neutral.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"map\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Vektorkarte<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Dichte Bereiche verhalten sich verl\u00e4sslicher.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"train\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Trainieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Sprachfluss wird statistisch optimiert.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"adapt\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Anpassen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Guter Einsatz braucht lokale Daten.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"test\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Testen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Durchschnittswerte verdecken Fehlerh\u00e4ufungen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"govern\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Steuern<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Kontrolle muss eingeplant sein.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-2-flow-panel-execution\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel\"\n\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\trole=\"tabpanel\" aria-labelledby=\"ns-aix-2-tab-execution\"\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps\" data-flow=\"execution\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"read\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Lesen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Menschliche Formulierung tritt in die Verarbeitung ein.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"tokenize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Tokenisieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">W\u00f6rter werden zu Fragmenten.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"vectorize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Vektorisieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Bedeutung wird zu Geometrie.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"contextualize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Kontext<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Attention formt Vektoren um.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"predict\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Vorhersagen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Sprachfluss entsteht Token f\u00fcr Token.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"confabulate\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Risiko<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Selbstsicherheit kann der Faktenlage vorauseilen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"ground\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Pr\u00fcfen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Kontrolle entsteht durch zus\u00e4tzliche Struktur.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t<div class=\"ns-aix-stage\" aria-label=\"Animiertes Vektorkarten-Prozessdiagramm\">\n\t\t\t\t<canvas class=\"ns-aix-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-on\" data-flow=\"development\" data-step=\"0\" data-key=\"collect\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>korpus<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"1\" data-key=\"split\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>tokens<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"2\" data-key=\"map\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>vektoren<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"3\" data-key=\"train\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>trainieren<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"4\" data-key=\"adapt\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>anpassen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"5\" data-key=\"test\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>test<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"development\" data-step=\"6\" data-key=\"govern\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>steuern<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"0\" data-key=\"read\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>eingabe<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"1\" data-key=\"tokenize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>tokens<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"2\" data-key=\"vectorize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>vektoren<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"3\" data-key=\"contextualize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>kontext<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"4\" data-key=\"predict\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>ausgabe<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"5\" data-key=\"confabulate\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>risiko<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"execution\" data-step=\"6\" data-key=\"ground\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pr\u00fcfen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<div class=\"ns-aix-handoff-panel\" role=\"status\" aria-live=\"polite\" aria-hidden=\"true\">\n\t\t\t\t\t<div class=\"ns-aix-handoff-rail\" aria-hidden=\"true\"><\/div>\n\t\t\t\t\t<div class=\"ns-aix-handoff-inner\">\n\t\t\t\t\t\t<span class=\"ns-aix-handoff-kicker\">Bereitstellung<\/span>\n\t\t\t\t\t\t<h4>Das Modell geht live<\/h4>\n\t\t\t\t\t\t<p>Alles in der Entwicklung geschieht einmalig vor dem Start. Von hier an l\u00e4uft dasselbe Modell f\u00fcr jede Nachricht, die ein Nutzer sendet \u2013 die folgenden Schritte wiederholen sich bei jeder Anfrage.<\/p>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\n\t\t<div class=\"ns-aix-controls\">\n\t\t\t<div class=\"ns-aix-dots\" role=\"navigation\" aria-label=\"Schrittnavigation\">\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset ns-on\"\n\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr Entwicklung &amp; Grundtraining\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot ns-on\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Sammeln\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Token-Regeln\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Vektorkarte\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Trainieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Anpassen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Testen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Steuern\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-development-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset\"\n\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr Umsetzung\"\n\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Lesen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Tokenisieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Vektorisieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Kontext\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Vorhersagen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Risiko\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Pr\u00fcfen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-2-panel-execution-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\n\t\t<div class=\"ns-aix-below\" aria-live=\"polite\">\n\t\t\t<div class=\"ns-aix-explain\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Text sammeln<\/h4>\n\t\t\t\t\t\t\t<p>Das Training beginnt mit gro\u00dfen Textsammlungen. Das Modell lernt die statistische Gestalt des Materials, das es sieht. Weil Korpora aus dem Web oft stark englischlastig sind, ist die Sprachabdeckung von Anfang an ungleich, sofern das Projekt nicht bewusst gegensteuert.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>Tokens zerlegen<\/h4>\n\t\t\t\t\t\t\t<p>Text wird vor dem Training in Tokens zerlegt, mit einem Vokabular, das selbst gelernt wurde \u2013 meist aus \u00fcberwiegend englischem Material. Manche Sprachen brauchen deshalb mehr Tokens f\u00fcr denselben Gedanken; Komposita, Flexion und seltener vertretene Schriften verbrauchen Kontext schneller und schw\u00e4chen das nachfolgende Schlussfolgern.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Vektoren abbilden<\/h4>\n\t\t\t\t\t\t\t<p>Tokens und Textabschnitte werden zu Vektoren. H\u00e4ufige Muster bilden dichte Nachbarschaften; seltene Sprache und Nischenthemen bilden d\u00fcnne Zonen, in denen der n\u00e4chste Treffer zu weit entfernt sein kann.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Vorhersage trainieren<\/h4>\n\t\t\t\t\t\t\t<p>Das Modell sagt wiederholt verdeckte oder n\u00e4chste Tokens vorher und passt seine Parameter an, wenn es falsch liegt. Kleine Modelle sind g\u00fcnstiger und schneller, haben aber weniger Kapazit\u00e4t; gro\u00dfe Modelle erfassen breitere Muster und mehr Sprachen, brauchen aber mehr Rechenleistung. Beide optimieren Vorhersage, nicht Wahrheit.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Lokal anpassen<\/h4>\n\t\t\t\t\t\t\t<p>Ein n\u00fctzliches Gesch\u00e4ftssystem braucht h\u00e4ufig sprachspezifisches Fine-Tuning, Ausrichtung an menschlichem Feedback, kuratierte Beispiele, Retrieval-Daten und Leitplanken. Das ist zus\u00e4tzlicher Aufwand, besonders au\u00dferhalb des Englischen und in Fachdom\u00e4nen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Schwachstellen testen<\/h4>\n\t\t\t\t\t\t\t<p>Die Evaluation muss dort ansetzen, wo das Modell am ehesten scheitert: Minderheitensprachen, Fachterminologie, seltene Entit\u00e4ten, mehrdeutige Formulierungen und Fragen mit d\u00fcnner Faktenlage.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-development-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"development\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Das Modell steuern<\/h4>\n\t\t\t\t\t\t\t<p>Protokollierung, Audits, Ablehnungsschwellen, menschliche Pr\u00fcfung und Update-Zyklen entscheiden, ob daraus ein kontrolliertes System wird oder eine eloquente Blackbox mit ungleichm\u00e4\u00dfiger Sprachleistung.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Text empfangen<\/h4>\n\t\t\t\t\t\t\t<p>Jemand schreibt eine Frage, ein Dokument trifft ein oder eine Kundin spricht mit einem Bot. Das System empf\u00e4ngt zuerst Zeichen, nicht Bedeutung.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>Tokens bilden<\/h4>\n\t\t\t\t\t\t\t<p>Der Text wird in W\u00f6rter, Wortteile, Satzzeichen oder Fragmente zerlegt. Diese Tokens werden auf numerische IDs abgebildet, bevor das Modell sie verarbeiten kann.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Vektoren nutzen<\/h4>\n\t\t\t\t\t\t\t<p>Jedes Token wird als hochdimensionaler Vektor dargestellt: als lange Zahlenliste. \u00c4hnliche Kontexte r\u00fccken Tokens nah zusammen. Das ist N\u00e4he, nicht Wahrheit.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Kontext anwenden<\/h4>\n\t\t\t\t\t\t\t<p>Die Attention im Transformer vergleicht jedes Token mit den umgebenden Tokens. Ein Wortvektor ver\u00e4ndert sich mit seinem Satz, doch das Modell lernt weiterhin Beziehungen und kein verankertes Weltmodell.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Ausgabe w\u00e4hlen<\/h4>\n\t\t\t\t\t\t\t<p>Das Modell sch\u00e4tzt, welches Token als N\u00e4chstes folgen sollte. Fl\u00fcssige Antworten entstehen aus wiederholten Wahrscheinlichkeitsentscheidungen, doch eine Faktenpr\u00fcfung ist nicht Teil des Erzeugungsmechanismus.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Risiko beachten<\/h4>\n\t\t\t\t\t\t\t<p>Ist die Faktenlage d\u00fcnn, liefert das Modell trotzdem die plausibelste Fortsetzung. Deshalb k\u00f6nnen Systeme \u00fcberzeugt klingen und dennoch Tatsachen erfinden, besonders in d\u00fcnn belegten Fachgebieten oder schw\u00e4cher vertretenen Sprachen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-2-panel-execution-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"execution\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Die Antwort verankern<\/h4>\n\t\t\t\t\t\t\t<p>Bessere Systeme bremsen das Modell mit Retrieval, Quellenpr\u00fcfung, Fachregeln oder menschlicher Kontrolle. R\u00fcckmeldungen aus dem Betrieb flie\u00dfen dann in Prompt-Design, Evaluationssets, Fine-Tuning und Governance. Verl\u00e4sslichkeit entsteht durch die Umsetzung, nicht durch das Sprachmodell allein.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"ns-aix-aspects\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset ns-on\" data-flow=\"development\" data-step=\"0\" aria-hidden=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Hintergrund<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>NLP geht auf die 1950er-Jahre und die regelbasierte maschinelle \u00dcbersetzung zur\u00fcck. In den 1990er- und 2000er-Jahren \u00fcbernahmen statistische Verfahren; Deep Learning und gro\u00dfe Sprachmodelle brachten den Durchbruch der 2010er-Jahre.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein Modell reproduziert jede Unwahrheit und jede Verzerrung, die im Trainingsmaterial steckt \u2013 der Korpus bestimmt das Ergebnis.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>NLP verbindet Sprachwissenschaft mit maschinellem Lernen: Systeme analysieren Grammatik (Syntax), Bedeutung (Semantik) und teils Absicht (Pragmatik).<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Derselbe Satz kann je nach Sprache sehr unterschiedlich viele Tokens kosten \u2013 ein praktischer Treiber f\u00fcr Kosten und Antwortqualit\u00e4t zugleich.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>W\u00f6rter und Wortteile werden in einen mehrdimensionalen Vektorraum abgebildet, der Bedeutungsmuster daraus erfasst, wie W\u00f6rter gemeinsam auftreten.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Halluzinationen h\u00e4ufen sich dort, wo das Quellenmaterial d\u00fcnn ist: In sp\u00e4rlichen Zonen kann der n\u00e4chste statistische Nachbar zu weit entfernt sein, um eine Tatsache abzubilden \u2013 das Modell antwortet trotzdem.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Modernes NLP beruht auf Transformern, die Sprache verarbeiten, indem sie Beziehungen zwischen W\u00f6rtern eines Satzes analysieren statt starrer Grammatikregeln.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Erzeugung zieht Stichproben aus Wahrscheinlichkeiten, deshalb kann derselbe Prompt in verschiedenen Sitzungen deutlich unterschiedliche Antworten liefern \u2013 behandeln Sie ein einzelnes KI-Urteil als eine Ziehung, nicht als feste Meinung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Kleine und gro\u00dfe Sprachmodelle werden zuerst auf allgemeine Sprache und Schlussfolgern trainiert, dann f\u00fcr einzelne Anwendungen feinjustiert und mit spezifischen, abrufbaren Daten unterst\u00fctzt.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Automatisierter Kundenservice, juristische Dokumentenpr\u00fcfung und die Analyse medizinischer Unterlagen h\u00e4ngen alle von dieser Anpassungsschicht ab, nicht vom Basismodell allein.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Gemessene Fehlerraten steigen stark, je schlechter ein Thema dokumentiert ist \u2013 von rund einem Prozent bei der Zusammenfassung kurzer Dokumente bis zur Mehrheit der Antworten bei speziellen Nischenfragen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Pr\u00fcfen Sie mit Fachleuten anhand Ihrer eigenen Dokumente und Sprachen, nicht nur mit \u00f6ffentlichen Benchmarks, die Durchschnittsleistung belohnen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"development\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Menschliche Aufsicht und kritische Bewertung sind unerl\u00e4sslich; Training und Betrieb gro\u00dfer Modelle werfen zudem Fragen zu Datenschutz, Desinformation und Missbrauch auf.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ohne Protokollierung und Pr\u00fcfung bleibt das System eloquent, aber nicht rechenschaftsf\u00e4hig \u2013 und seine Sprachleistung bleibt dort ungleich, wo niemand misst.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"0\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was NLP leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Sprachen \u00fcbersetzen, lange Texte zusammenfassen, Kerninformationen extrahieren, Stimmungen analysieren und Dialogsysteme betreiben \u2013 mit deutlich weniger manuellem Aufwand bei textlastiger Arbeit.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Spracherkennung und Sprachsynthese erweitern dieselbe Verarbeitungskette auf die gesprochene Interaktion mit Maschinen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Text betritt und verl\u00e4sst ein Sprachmodell nie als Text. Er wird in Wortteil-Fragmente zerlegt, die je einer ganzzahligen ID zugeordnet werden.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Alles, was das Modell \u00fcber Ihren Text \u201ewei\u00df\u201c, gelangt \u00fcber diese Fragmente hinein \u2013 sonst nichts.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Jeder Vektor ist typischerweise tausende Zahlen lang. Das Training justiert Milliarden Parameter, damit Tokens aus \u00e4hnlichen Kontexten mathematisch \u00e4hnliche Vektoren erhalten.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>An keiner Stelle pr\u00fcft das System etwas gegen die Wahrheit \u2013 es pr\u00fcft N\u00e4he. Zwei Schreibweisen eines Namens sind als Vektoren nahezu identisch; die statistisch wahrscheinlichere gewinnt.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Attention l\u00e4sst den Vektor eines Wortes mit seinem Satz verschieben \u2013 der Grund, warum dasselbe Wort in verschiedenen Kontexten Verschiedenes bedeuten kann.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das Modell lernt statistische Beziehungen zwischen W\u00f6rtern und Wendungen, kein verankertes Verst\u00e4ndnis der Welt, die sie beschreiben.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das Modell w\u00e4hlt wiederholt ein wahrscheinliches n\u00e4chstes Token, bis die Antwort vollst\u00e4ndig ist. Kleine statistische Unterschiede am Anfang k\u00f6nnen sich zu einer v\u00f6llig anderen Gesamtantwort aufschaukeln.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Selbstsicherheit steckt im Erzeugungsstil und hat nichts mit der G\u00fcltigkeit des Inhalts zu tun \u2013 das System klingt genauso \u00fcberzeugt, wenn es r\u00e4t.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Fehler h\u00e4ufen sich genau bei den Themen, die Nutzende am wenigsten \u00fcberpr\u00fcfen k\u00f6nnen. Skepsis sollte deshalb umgekehrt proportional zur eigenen Fachkenntnis wachsen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Dieselbe Frage mehrfach in neuen Sitzungen zu stellen und die Antworten zu vergleichen zeigt, wo ein Modell auf sicherem Boden steht und wo es r\u00e4t.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"execution\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Verl\u00e4sslichkeit ist eine Eigenschaft der Umsetzung: Retrieval, Quellenpr\u00fcfung, Fachregeln und menschliche Kontrolle werden um das Modell herum erg\u00e4nzt \u2013 im Modell selbst stecken sie nicht.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ist die Retrieval-\u00c4hnlichkeit gering, entscheidet ein gut gebautes System im Zweifel f\u00fcr Vorsicht: Es verwirft die Antwort oder weist ausdr\u00fccklich auf geringe Sicherheit hin, statt zu raten.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_17 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_10 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><h3>The Challenges<\/h3>\n<p data-start=\"3434\" data-end=\"3776\">No matter how \"human\" they sound, NLP systems face important system-defined limitations. They can easily produce fluent but factually incorrect or misleading information. They also reproduce any falsehood or bias in the information available when trained.<\/p>\n<p data-start=\"3434\" data-end=\"3776\">As NLP systems are solely based on statistical patterns and have only limited contextual understanding, they can struggle with reasoning, and consistency. Also, they are solely based on the input provided during training and feedback during operations. This is particularly problematic with large open models.<\/p>\n<p data-start=\"3778\" data-end=\"4217\" data-is-last-node=\"\" data-is-only-node=\"\">Training large models requires significant resources and raises concerns about privacy, misinformation, and misuse. Human supervision and critical evaluation are thus essential.<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_11 et_pb_row et_flex_row\" style=\"--ns-caro-top:26px\">\n<div class=\"et_pb_column_18 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_code_5 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\"><div class=\"nsp-frame nsp-frame--transparent\"><div class=\"nsp-frame-head\"><h2>Featured Projects<\/h2><\/div><div class=\"nsp-carousel-wrap\" data-base-width=\"240\" data-loop=\"1\"><button type=\"button\" class=\"nsp-nav nsp-prev\" aria-label=\"Previous\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x34;<\/span><\/button><div class=\"nsp-carousel\">\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"3\" aria-label=\"RAG-driven Legal Chatbot\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-section\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">RAG-driven Legal Chatbot<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">A small-to-medium language model reliably answering German legal questions based on a strong RAG pipeline.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"7\" aria-label=\"Generative AI Audit Framework\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Generative AI Audit Framework<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Development of a structured Generative AI audit framework. This included establishing a methodology for Level 1 and Level 2 GenAI audits<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"12\" aria-label=\"Intelligent Data Retrieval Agent\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Intelligent Data Retrieval Agent<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Production-ready AI retrieval system using LLMs and semantic search to transform fragmented data into reliable, searchable knowledge.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"23\" aria-label=\"RAG-Based Enterprise Knowledge Assistant\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-regular fa-folder-open\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">RAG-Based Enterprise Knowledge Assistant<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Designed RAG-based AI assistants that turn fragmented documents and expert knowledge into accessible, context-aware enterprise knowledge.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"2\" aria-label=\"Customer Interaction Analysis\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Customer Interaction Analysis<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">SaaS project platform: the objective was to evaluate dialogue quality using an AI model to ensure timely intervention and customer care.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t<\/div><button type=\"button\" class=\"nsp-nav nsp-next\" aria-label=\"Next\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x35;<\/span><\/button><\/div><script>(function(){\n\t\t\tif (!window.nspComputeLayout) {\n\t\t\t\twindow.NSP_BASE_CARD_WIDTH = 240;\n\t\t\t\twindow.nspIsFluidWidth = function(){ return window.innerWidth > 640; };\n\t\t\t\twindow.nspComputeLayout = function(available, gap, totalCards, baseWidth){\n\t\t\t\t\tvar BASE = baseWidth || window.NSP_BASE_CARD_WIDTH;\n\t\t\t\t\tavailable = Math.max(0, available || 0);\n\t\t\t\t\tgap = Math.max(0, gap || 0);\n\t\t\t\t\ttotalCards = Math.max(0, totalCards || 0);\n\t\t\t\t\tif (!totalCards){\n\t\t\t\t\t\treturn { count: 0, width: BASE, center: true };\n\t\t\t\t\t}\n\t\t\t\t\tvar per = BASE + gap;\n\t\t\t\t\tvar baseCount = Math.max(1, Math.floor((available + gap) \/ per));\n\t\t\t\t\tvar used = baseCount * BASE + (baseCount - 1) * gap;\n\t\t\t\t\tvar remainder = available - used;\n\t\t\t\t\t\/\/ Only create an extra visible slot when there is actually another card to fill it.\n\t\t\t\t\t\/\/ If exactly the base-width row count is present, distribute those cards evenly\n\t\t\t\t\t\/\/ across the row instead of leaving them beside a phantom extra slot.\n\t\t\t\t\tvar fullCount = (totalCards > baseCount && remainder >= (2 \/ 3) * BASE) ? baseCount + 1 : baseCount;\n\t\t\t\t\tfullCount = Math.max(1, fullCount);\n\t\t\t\t\tvar fullWidth = (available - (fullCount - 1) * gap) \/ fullCount;\n\t\t\t\t\tif (!isFinite(fullWidth) || fullWidth <= 0){ fullWidth = BASE; }\n\n\t\t\t\t\t\/\/ One or two cards should never grow just because the row is wide.\n\t\t\t\t\t\/\/ They keep the base width, sit at the left, and leave the rest of the row empty.\n\t\t\t\t\tif (totalCards < 3){\n\t\t\t\t\t\tvar smallMax = (available - (totalCards - 1) * gap) \/ totalCards;\n\t\t\t\t\t\tvar smallWidth = (isFinite(smallMax) && smallMax > 0) ? Math.min(BASE, smallMax) : BASE;\n\t\t\t\t\t\treturn { count: totalCards, width: smallWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\t\/\/ If there are fewer cards than a full row would hold, keep the full-row\n\t\t\t\t\t\/\/ card width rather than stretching those few across the whole row, and\n\t\t\t\t\t\/\/ leave the remaining slots empty. Left-aligned, as the master grid is.\n\t\t\t\t\tif (totalCards < fullCount){\n\t\t\t\t\t\treturn { count: totalCards, width: fullWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\tvar count = Math.min(fullCount, totalCards);\n\t\t\t\t\treturn { count: count, width: fullWidth, center: false };\n\t\t\t\t};\n\t\t\t\t\/\/ Centre the chevrons on the media block of a card rather than on\n\t\t\t\t\/\/ the whole card: on people cards that is the square photo\n\t\t\t\t\/\/ (whose height tracks the fluid card width, so it cannot be\n\t\t\t\t\/\/ expressed in CSS), on project cards the icon block. Published\n\t\t\t\t\/\/ as a custom property the stylesheet reads.\n\t\t\t\twindow.nspTrackPadX = function(track){\n\t\t\t\t\tvar cs = window.getComputedStyle(track);\n\t\t\t\t\treturn (parseFloat(cs.paddingLeft) || 0) + (parseFloat(cs.paddingRight) || 0);\n\t\t\t\t};\n\t\t\t\twindow.nspSyncNav = function(wrap){\n\t\t\t\t\t\/\/ People cards anchor on the photo, which is the visual mass of\n\t\t\t\t\t\/\/ the card. Project cards have no photo -- only a small icon\n\t\t\t\t\t\/\/ at the top -- so they anchor on the card panel itself and\n\t\t\t\t\t\/\/ the arrows land on its vertical centre. Measuring against\n\t\t\t\t\t\/\/ the wrap in viewport coordinates absorbs the track padding\n\t\t\t\t\t\/\/ and card margins without restating any of them here.\n\t\t\t\t\tvar media = wrap.querySelector(\".nsp-card-photo\")\n\t\t\t\t\t\t|| wrap.querySelector(\".nsp-card\");\n\t\t\t\t\tif (!media){ return; }\n\t\t\t\t\tvar r = media.getBoundingClientRect();\n\t\t\t\t\tif (!r.height){ return; }\n\t\t\t\t\tvar w = wrap.getBoundingClientRect();\n\t\t\t\t\twrap.style.setProperty(\"--nsp-nav-top\", ((r.top - w.top) + r.height \/ 2) + \"px\");\n\t\t\t\t};\n\t\t\t}\n\t\t\tvar wrap = document.currentScript.previousElementSibling;\n\t\t\tif(!wrap){ return; }\n\t\t\t\/\/ The frame carries the visible panel, so it has to be revealed\n\t\t\t\/\/ together with the wrap -- otherwise an empty framed box paints\n\t\t\t\/\/ before the cards have been sized into it.\n\t\t\tfunction reveal(w){\n\t\t\t\tw.style.visibility = \"visible\";\n\t\t\t\tvar f = w.parentNode;\n\t\t\t\tif (f && f.classList && f.classList.contains(\"nsp-frame\")){ f.style.visibility = \"visible\"; }\n\t\t\t}\n\t\t\tvar baseWidth = parseInt(wrap.getAttribute(\"data-base-width\"), 10) || window.NSP_BASE_CARD_WIDTH;\n\t\t\tvar track = wrap.querySelector(\".nsp-carousel\");\n\t\t\tvar cards = track ? track.querySelectorAll(\".nsp-card\") : [];\n\t\t\tif(!track || !cards.length){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\/\/ Read from the stylesheet rather than restating it: a hard-coded copy\n\t\t\t\/\/ here is exactly how the gutter drifted from the CSS before.\n\t\t\tvar gap = parseFloat(window.getComputedStyle(track).columnGap) || 24;\n\t\t\tif (!window.nspIsFluidWidth()) {\n\t\t\t\t\/\/ Mobile: unchanged -- fixed per-card width (CSS 82vw), just avoid a partial\n\t\t\t\t\/\/ card peeking out at the wrap edge.\n\t\t\t\tvar cardW = cards[0].getBoundingClientRect().width;\n\t\t\t\tif(!cardW){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\t\/\/ clientWidth is the PADDING box, so the track padding has to come\n\t\t\t\t\/\/ off before this is the room the cards actually get.\n\t\t\t\tvar available0 = track.clientWidth - window.nspTrackPadX(track);\n\t\t\t\tvar fitCount = Math.max(1, Math.floor((available0 + gap) \/ (cardW + gap)));\n\t\t\t\tvar count0 = Math.min(fitCount, cards.length);\n\t\t\t\tvar needed0 = count0 * cardW + (count0 - 1) * gap;\n\t\t\t\tvar ws0 = window.getComputedStyle(wrap);\n\t\t\t\tvar padX0 = (parseFloat(ws0.paddingLeft) || 0) + (parseFloat(ws0.paddingRight) || 0);\n\t\t\t\tvar target0 = needed0 + window.nspTrackPadX(track) + (ws0.boxSizing === \"border-box\" ? padX0 : 0);\n\t\t\t\twrap.style.maxWidth = Math.ceil(target0) + \"px\";\n\t\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t\/\/ Desktop\/tablet: fluid card width, filling the row exactly either way.\n\t\t\t\/\/ clientWidth is the PADDING box -- take the track padding off it.\n\t\t\tvar available = track.clientWidth - window.nspTrackPadX(track);\n\t\t\tvar layout = window.nspComputeLayout(available, gap, cards.length, baseWidth);\n\t\t\tfor (var i = 0; i < cards.length; i++){ cards[i].style.flex = \"0 0 \" + layout.width + \"px\"; }\n\t\t\tif (layout.center) {\n\t\t\t\tvar totalW = layout.count * layout.width + (layout.count - 1) * gap;\n\t\t\t\twrap.style.maxWidth = Math.ceil(totalW + window.nspTrackPadX(track)) + \"px\";\n\t\t\t\twrap.style.marginLeft = \"auto\";\n\t\t\t\twrap.style.marginRight = \"auto\";\n\t\t\t}\n\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t})();<\/script><\/div><noscript><style>.nsp-carousel-wrap,.nsp-frame{visibility:visible !important;}<\/style><\/noscript><div class=\"nsp-popups\" hidden><template class=\"nsp-popup-tpl\" data-id=\"3\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-section\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">RAG-driven Legal Chatbot<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>An AI-supported RAG-Chatbot developed for legal and administrative workflows. Designed to support caseworkers in navigating complex regulations - currently focused on German Social Welfare - the system provides fast, contextual access to relevant legal information and assists in decision-making for applications and case management. The modular architecture allows seamless expansion into additional legal domains and regulatory frameworks.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"7\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Generative AI Audit Framework<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Development of a multidimensional Blackbox Chatbot Audit framework for evaluating chatbot user experience and business value in customer service environments. The audit methodology combines structured use-case testing with qualitative and quantitative evaluation dimensions, including answer quality, response speed, dialogue quality, and user interface assessment.<\/p>\n<p>The framework also incorporates hallucination testing and edge-case analysis to assess robustness and real-world usability. The project included extensive market and user-frustration research, methodology development, pilot implementation, and iterative testing and retesting phases. The resulting audit framework is used to evaluate chatbot performance, identify optimization potential, and assess user retention likelihood and overall business impact.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/governance-and-ethics\">Governance<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"12\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe0f7;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Intelligent Data Retrieval Agent<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Development of a production-ready retrieval agent for querying large, fragmented, and undocumented enterprise data repositories using large language models and semantic search. The solution transformed scattered legacy records into structured, searchable knowledge, enabling users to retrieve relevant information within seconds instead of manually searching across hundreds of documents.<\/p>\n<p>The project combined retrieval-augmented generation (RAG), vector search, and modern LLM technologies to deliver reliable, context-aware information retrieval. Designed with a modular architecture, the system supports scalability, maintainability, and future extensions while ensuring robust retrieval quality across heterogeneous data sources.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>AI Engineer<\/p>\n<p>Python \u2022 LangChain \u2022 OpenAI \u2022 Qdrant \u2022 Semantic Search \u2022 RAG \u2022 Streamlit<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"23\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-regular fa-folder-open\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">RAG-Based Enterprise Knowledge Assistant<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Gerold designed and developed concepts and prototypes for RAG-based AI assistants that make fragmented organizational knowledge accessible through natural-language interaction.<\/p>\n<p>The solutions combine internal documents, structured information and expert knowledge with Large Language Models, semantic search and retrieval-augmented generation. The focus is not only on the underlying technology, but on creating a reliable end-to-end solution: from identifying and structuring relevant knowledge sources to retrieval architecture, user experience, access concepts and governance.<\/p>\n<p>The work demonstrates how Generative AI can transform static document repositories into practical knowledge systems that support employees in finding information faster, preserving expert knowledge and making better-informed decisions.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>AI Strategy &amp; Solution Design, Generative AI, LLMs, RAG, Prompt Design, Knowledge Management<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/ai-strategy\">AI Strategy<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/consulting\">AI Transformation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"2\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#x77;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">Customer Interaction Analysis<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a project management SaaS solution where customers were matched with freelancers, a custom AI solution was established with the purpose to improve experiences for all parties. Key purposes were to create an early warning system to help customer service intervene in case of issues:<\/p>\n<ul>\n<li>Identification of unusual patterns (delays indicating inaction, intense exchanges);<\/li>\n<li>Flagging of language transgressions on both sides (use of inappropriate language, aggression);<\/li>\n<li>Matching of final ratings with evaluation of flow and dialogue quality to foster a more honest rating culture;<\/li>\n<li>Language style matching to improve future matching of freelancers to clients;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was implemented using Python on a LAMP stack, with self-developed machine learning libraries.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/nlp\">Natural Language Processing<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><\/div><div class=\"nsp-overlay\" id=\"nsp-overlay\" role=\"dialog\" aria-modal=\"true\"><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_7 et_pb_section et_section_regular et_flex_section ns-panel\" id=\"cv\" style=\"--ns-rail-w:264px; --ns-body-color:#D3D3D3;\">\n<div class=\"et_pb_row_12 et_pb_row et_flex_row\">\n<div class=\"et_pb_column_19 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_11 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><p>As formidable as the interplay of the human eye, brain and muscles is, it evolved to focus on what matters and filter out the rest. Machine vision has no such filter: it inspects every pixel with the same attention, frame after frame, around the clock. It never gets tired, and it works reliably in environments where humans are unsafe or uncomfortable.<\/p>\n<\/div><\/div>\n\n<div class=\"et_pb_code_6 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\">\t<div\n\t\tid=\"ns-aix-3\"\n\t\tclass=\"ns-aix ns-aix-cv\"\n\t\tdata-topic=\"cv\"\n\t\tdata-flow=\"core\"\n\t\t\t\tdata-step=\"0\"\n\t\tdata-interval=\"9000\"\n\t\t\t\tdata-autoplay=\"1\"\n\t\trole=\"region\"\n\t\taria-label=\"So funktioniert Bildverarbeitung\"\n\t\tstyle=\"--ns-aix-accent:#58a7f9;--ns-aix-secondary:#2b6cb0\"\n\t>\n\t\t<header class=\"ns-aix-head\">\n\t\t\t\t\t\t<h3 class=\"ns-aix-title\">So funktioniert Bildverarbeitung<\/h3>\n\t\t\t<p class=\"ns-aix-intro\">Bildverarbeitung wandelt visuelle Signale in numerische Daten um \u2013 ein Bild ist ein Zahlenraster \u2013, extrahiert dann aufgabenrelevante Muster und erzeugt strukturierte Ausgaben wie Bezeichnungen, Positionen, Masken, Text, Messwerte oder Bewegung. Sie sieht nicht wie ein Mensch; sie sch\u00e4tzt Wahrscheinlichkeiten aus visuellen Hinweisen, die f\u00fcr einen bestimmten Zweck gelernt wurden.<\/p>\n\t\t\t\t\t\t\t\t<\/header>\n\n\t\t<div class=\"ns-aix-body\">\n\t\t\t<div class=\"ns-aix-copy\">\n\t\t\t\t<div class=\"ns-aix-progress\" aria-hidden=\"true\"><span><\/span><\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-3-flow-panel-core\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel ns-on\"\n\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps ns-on\" data-flow=\"core\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step ns-on\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"capture\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Erfassen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Licht und andere Signale werden zur Eingabe.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"encode\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Kodieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Pixel, Kan\u00e4le und Einzelbilder.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"prepare\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Aufbereiten<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Rauschen, Ma\u00dfstab und Blickwinkel korrigieren.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"learn\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Lernen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Kanten werden zu Formen und Objekten.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"recognize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Erkennen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Klassifizieren, erkennen und Anomalien finden.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"map\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Kartieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Masken, Landmarken, Tiefe und Text.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"track\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verfolgen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Identit\u00e4t und Bewegung bleiben \u00fcber Einzelbilder hinweg erhalten.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\t\tdata-key=\"act\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-7\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">08<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Handeln<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Messen, z\u00e4hlen, alarmieren oder steuern.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\t\tdata-step=\"8\"\n\t\t\t\t\t\t\t\t\tdata-key=\"validate\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-8\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">09<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Validieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Leistung, Verzerrung, Drift und Aufsicht.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t<div class=\"ns-aix-stage\" aria-label=\"Animiertes Vektorkarten-Prozessdiagramm\">\n\t\t\t\t<canvas class=\"ns-aix-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-on\" data-flow=\"core\" data-step=\"0\" data-key=\"capture\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>sensor<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"1\" data-key=\"encode\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pixel<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"2\" data-key=\"prepare\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>aufbereiten<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"3\" data-key=\"learn\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>merkmale<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"4\" data-key=\"recognize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>erkennen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"5\" data-key=\"map\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>karte<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"6\" data-key=\"track\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>verfolgen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"7\" data-key=\"act\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>handeln<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"core\" data-step=\"8\" data-key=\"validate\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pr\u00fcfen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t<\/div>\n\n\t\t<div class=\"ns-aix-controls\">\n\t\t\t<div class=\"ns-aix-dots\" role=\"navigation\" aria-label=\"Schrittnavigation\">\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset ns-on\"\n\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr So funktioniert Bildverarbeitung\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot ns-on\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Erfassen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Kodieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Aufbereiten\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Lernen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Erkennen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Kartieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Verfolgen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 8: Handeln\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-7\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\t\tdata-step=\"8\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 9: Validieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-3-panel-core-8\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\n\t\t<div class=\"ns-aix-below\" aria-live=\"polite\">\n\t\t\t<div class=\"ns-aix-explain\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Die Szene vermessen<\/h4>\n\t\t\t\t\t\t\t<p>Bildverarbeitung beginnt mit einem Sensor: einer Kamera, einem Scanner, Mikroskop, Satelliten, R\u00f6ntgenger\u00e4t, einer W\u00e4rmebildkamera oder einem Tiefensensor. Objektiv, Blickwinkel, Belichtung, Aufl\u00f6sung und Bildrate bestimmen, welche Information ins System gelangt. Details, die nie erfasst wurden, lassen sich sp\u00e4ter nicht verl\u00e4sslich rekonstruieren.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>In Pixel kodieren<\/h4>\n\t\t\t\t\t\t\t<p>Ein digitales Bild ist ein Raster aus Pixeln. Jedes Pixel speichert Kanalwerte wie Rot, Gr\u00fcn und Blau, Graustufenintensit\u00e4t, Infrarotantwort oder Tiefe. Video f\u00fcgt Zeit als Abfolge von Einzelbildern hinzu. Aufl\u00f6sung, Farbtiefe und Kompression bestimmen, wie viel visuelle Information erhalten bleibt oder verworfen wird.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Die Eingabe aufbereiten<\/h4>\n\t\t\t\t\t\t\t<p>Bilder k\u00f6nnen skaliert, zugeschnitten, entrauscht, gesch\u00e4rft, von Objektiv- oder Perspektivverzerrung befreit und in Farbe oder Beleuchtung normalisiert werden. Trainingsdaten werden oft mit realistischer Variation angereichert. Die Aufbereitung sollte zu den Betriebsbedingungen passen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Visuelle Muster lernen<\/h4>\n\t\t\t\t\t\t\t<p>Klassische Bildverarbeitung st\u00fctzt sich auf konstruierte Kanten, Ecken und Vorlagen. Moderne Faltungsnetze und Vision-Transformer lernen Merkmalshierarchien aus Beispielen: Einfache Kontrastmuster verbinden sich zu Texturen, Formen, Teilen und r\u00e4umlichen Beziehungen. Dieses Lernen findet einmal statt, vor dem Einsatz.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Objekte und Anomalien erkennen<\/h4>\n\t\t\t\t\t\t\t<p>Bildklassifikation weist einem ganzen Bild eine Bezeichnung zu. Objekterkennung findet einzelne Instanzen und ihre Positionen, meist mit Begrenzungsrahmen und Konfidenzwerten. Anomalieerkennung lernt stattdessen, wie normale Bilddaten aussehen, und meldet Abweichungen. Ein hoher Konfidenzwert ist nicht dasselbe wie eine hohe Wahrscheinlichkeit, richtig zu liegen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Regionen, Tiefe und Text kartieren<\/h4>\n\t\t\t\t\t\t\t<p>Segmentierung ordnet Pixeln eine Kategorie oder Objektidentit\u00e4t zu. Keypoint- und Pose-Modelle finden Landmarken; Tiefenmodelle sch\u00e4tzen Abstand und dreidimensionale Struktur; OCR- und Layoutsysteme rekonstruieren Zeichen, Felder und Lesereihenfolge.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Objekte \u00fcber die Zeit verfolgen<\/h4>\n\t\t\t\t\t\t\t<p>Videosysteme verkn\u00fcpfen Erkennungen \u00fcber Einzelbilder hinweg, damit ein Objekt eine stabile Identit\u00e4t beh\u00e4lt. Aus den Trajektorien lassen sich Richtung, Geschwindigkeit, Durchsatz, Verweildauer und Handlungen sch\u00e4tzen oder Objekte z\u00e4hlen, die eine Grenze \u00fcberqueren.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-7\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">08<\/span>Wahrnehmung in Handlung \u00fcberf\u00fchren<\/h4>\n\t\t\t\t\t\t\t<p>Die Ausgabe der Bildverarbeitung wird n\u00fctzlich, wenn ein anderer Prozess sie verwendet: ein Objekt z\u00e4hlen oder sortieren, eine Datentabelle f\u00fcllen, Personal alarmieren, Wartung ausl\u00f6sen oder einen Roboter f\u00fchren. Schwellenwerte machen aus Wahrscheinlichkeiten Handlungen. Geht es um Menschen, begrenzen Datenschutz und Einwilligung, was das System erfassen, speichern und daraus ableiten darf.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-3-panel-core-8\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"core\"\n\t\t\t\t\t\t\tdata-step=\"8\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">09<\/span>In der realen Welt testen<\/h4>\n\t\t\t\t\t\t\t<p>Ein Bildverarbeitungssystem muss auf separaten Daten getestet werden \u2013 \u00fcber Beleuchtung, Wetter, Kamerapositionen, demografische Gruppen, seltene F\u00e4lle und absichtliche St\u00f6rungen hinweg. Pr\u00e4zision, Trefferquote, falsch Positive, falsch Negative, Latenz und Kalibrierung sind dabei alle relevant. Monitoring und menschliche Korrekturen erkennen Drift und verbessern das System auf sichere Weise.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"ns-aix-aspects\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset ns-on\" data-flow=\"core\" data-step=\"0\" aria-hidden=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Hintergrund<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die fr\u00fche Bildverarbeitung begann in den 1960er- und 1970er-Jahren mit Programmen, die einfache Formen erkannten \u2013 und mit der optischen Zeichenerkennung (OCR) f\u00fcr maschinengeschriebene Dokumente als einer der ersten praktischen Anwendungen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Kamerawahl, Platzierung und Beleuchtung entscheiden oft \u00fcber den Projekterfolg, bevor \u00fcberhaupt ein Modell trainiert wird.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Bildverarbeitungssysteme gewinnen Bedeutung aus Pixeln, die als Zahlenwerte vorliegen, und erkennen Muster in diesen Zahlen, um Objekte, Formen, Texturen und Bewegung zu identifizieren.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Kompression und niedrige Aufl\u00f6sung verwerfen unbemerkt Information, die das Modell sp\u00e4ter brauchen k\u00f6nnte \u2013 was hier verloren geht, ist endg\u00fcltig verloren.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Im Training bekommt das Modell viele beschriftete Beispiele gezeigt, trifft Vorhersagen, vergleicht sie mit den richtigen Bezeichnungen und passt interne Parameter an, um Fehler zu verringern.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Zu starke Bereinigung kann genau den Defekt oder das Signal entfernen, das das System finden soll.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Hintergrund<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>In den 2000er-Jahren beschleunigte sich der Fortschritt durch bessere Hardware und gro\u00dfe Datens\u00e4tze; ein wichtiger Durchbruch kam 2012, als Deep Learning die Erkennungsgenauigkeit deutlich verbesserte.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Tiefe neuronale Netze lernen visuelle Muster direkt aus gro\u00dfen Sammlungen beschrifteter Bilder, statt sich auf handgeschriebene Regeln zu st\u00fctzen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was Bildverarbeitung leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Unregelm\u00e4\u00dfigkeiten an Fertigungslinien finden, Eindringlinge erkennen, Objekte kategorisieren und Gesichter erkennen \u2013 oft mit Unterschieden, die das menschliche Auge \u00fcbersieht.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Genauigkeit kann zwischen demografischen Gruppen schwanken, wenn die Trainingsdaten verzerrt sind \u2013 ein bekanntes und ernstes Risiko bei Gesichtserkennung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was Bildverarbeitung leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>OCR in Kombination mit KI kann nahezu jedes Gesch\u00e4ftsdokument erfassen, Datentabellen zuverl\u00e4ssig bef\u00fcllen und Entscheidungen \u00fcber den weiteren Umgang mit der Eingabe unterst\u00fctzen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Segmentierung, Landmarken und Tiefe unterst\u00fctzen Aufgaben in Messung, Pr\u00fcfung, Navigation und Dokumentenverarbeitung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was Bildverarbeitung leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Menschen in Menschenmengen z\u00e4hlen, Objekte bei Nacht oder hoher Geschwindigkeit verfolgen, Durchsatz messen \u2013 oft als Ersatz f\u00fcr teure Sensorik oder stundenlange menschliche Arbeit.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Verdeckung, Bewegungsunsch\u00e4rfe, Kamerabewegung und wieder auftauchende Objekte k\u00f6nnen eine Verfolgung abrei\u00dfen lassen und Z\u00e4hlungen verf\u00e4lschen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"7\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das System \u201eerkennt\u201c Objekte nicht im menschlichen Sinn \u2013 es berechnet Wahrscheinlichkeiten aus gelernten visuellen Mustern, was zu gef\u00e4hrlichen Fehlern f\u00fchren kann, wenn man ihnen blind folgt.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Kosten eines \u00fcbersehenen Ereignisses gegen\u00fcber denen eines Fehlalarms sollten entscheiden, wann die Automatisierung handelt und wann ein Mensch pr\u00fcft.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"core\" data-step=\"8\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Bildverarbeitungssysteme tun sich schwer mit unbekannten Objekten, ungewohnten Bedingungen und \u00dcberlappung; Drift entsteht, wenn sich die Welt um ein eingefrorenes Modell herum ver\u00e4ndert.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>In regulierten oder sicherheitsrelevanten Anwendungen machen dokumentierte Testergebnisse \u00fcber Bedingungen und demografische Gruppen hinweg aus einer funktionierenden Demo ein System, das vertrauensw\u00fcrdig und pr\u00fcfbar ist.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_20 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_12 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><h3>The Challenges<\/h3>\n<p>Despite their capabilities often surpassing human vision, Computer Vision systems have limitations. They struggle with unknown information, unfamiliar conditions, or overlapping objects. Equally, while they can even detect the smallest changes, learning what is relevant and what isn\u2019t can be hard.<\/p>\n<p>Another concern is bias, for example, when it comes to facial recognition. Often, due to biased training data, their accuracy varies across different ethnic groups. And ultimately, they do not \u201crecognize\u201d items, but only statistical patterns. This can create dangerous errors, for example in facial recognition. As with all tools, careful oversight and governance are required.<\/p>\n<p>Additionally, the challenges emerging from image generation create entirely new ethical and regulatory problems.<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_row_13 et_pb_row et_flex_row\" style=\"--ns-caro-top:26px\">\n<div class=\"et_pb_column_21 et_pb_column et-last-child et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_code_7 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\"><div class=\"nsp-frame nsp-frame--transparent\"><div class=\"nsp-frame-head\"><h2>Featured Projects<\/h2><\/div><div class=\"nsp-carousel-wrap\" data-base-width=\"240\" data-loop=\"1\"><button type=\"button\" class=\"nsp-nav nsp-prev\" aria-label=\"Previous\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x34;<\/span><\/button><div class=\"nsp-carousel\">\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"10\" aria-label=\"International Process Digitalization in Facility Management\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe035;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">International Process Digitalization in Facility Management<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Transformation and standardization of international facility management processes through the introduction of scalable structures.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"11\" aria-label=\"ERP\/CRM Product Development &amp; Process Digitalization\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><span class=\"nsp-card-icon et-pb-icon\" aria-hidden=\"true\">&#xe00d;<\/span><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">ERP\/CRM Product Development &amp; Process Digitalization<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Development and implementation of a modular ERP\/CRM system to digitalize central business processes.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"13\" aria-label=\"Visual Search Recommendations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-socks\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Search Recommendations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">eCommmerce plugin that enables searching for visually similar products, helping customers to find and compare multiple related items.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"14\" aria-label=\"Visual Assistance for Seniors\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-glasses\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Visual Assistance for Seniors<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Visual Assistance App: enabling visual assistance for seniors by helping position determination using Computer Vision and Deep Learning.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"1\" aria-label=\"Electrical Switch Monitor\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-toggle-on\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Electrical Switch Monitor<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Public transportation: using AI-driven vision to monitor old-fashioned electrical relays and also to evaluate potential failures for predictive maintenance.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t\t\t<article class=\"nsp-card\" tabindex=\"0\" role=\"button\" data-id=\"5\" aria-label=\"Hydropower Plant Operations\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-card-iconwrap\"><i class=\"nsp-card-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i><\/div>\n\t\t\t\t\t\t<h3 class=\"nsp-card-title\">Hydropower Plant Operations<\/h3>\n\t\t\t\t\t\t\t\t\t\t<p class=\"nsp-card-excerpt\">Create a control and monitoring solution for all plant operations, including predictive maintenance logic and intrusion mon\u00aditoring.<\/p>\n\t\t\t\t\t\t\t\t\t\t<span class=\"nsp-card-more\">read more\u2026<\/span>\n\t\t\t\t\t<\/article>\n\t\t<\/div><button type=\"button\" class=\"nsp-nav nsp-next\" aria-label=\"Next\"><span class=\"nsp-nav-icon et-pb-icon\" aria-hidden=\"true\">&#x35;<\/span><\/button><\/div><script>(function(){\n\t\t\tif (!window.nspComputeLayout) {\n\t\t\t\twindow.NSP_BASE_CARD_WIDTH = 240;\n\t\t\t\twindow.nspIsFluidWidth = function(){ return window.innerWidth > 640; };\n\t\t\t\twindow.nspComputeLayout = function(available, gap, totalCards, baseWidth){\n\t\t\t\t\tvar BASE = baseWidth || window.NSP_BASE_CARD_WIDTH;\n\t\t\t\t\tavailable = Math.max(0, available || 0);\n\t\t\t\t\tgap = Math.max(0, gap || 0);\n\t\t\t\t\ttotalCards = Math.max(0, totalCards || 0);\n\t\t\t\t\tif (!totalCards){\n\t\t\t\t\t\treturn { count: 0, width: BASE, center: true };\n\t\t\t\t\t}\n\t\t\t\t\tvar per = BASE + gap;\n\t\t\t\t\tvar baseCount = Math.max(1, Math.floor((available + gap) \/ per));\n\t\t\t\t\tvar used = baseCount * BASE + (baseCount - 1) * gap;\n\t\t\t\t\tvar remainder = available - used;\n\t\t\t\t\t\/\/ Only create an extra visible slot when there is actually another card to fill it.\n\t\t\t\t\t\/\/ If exactly the base-width row count is present, distribute those cards evenly\n\t\t\t\t\t\/\/ across the row instead of leaving them beside a phantom extra slot.\n\t\t\t\t\tvar fullCount = (totalCards > baseCount && remainder >= (2 \/ 3) * BASE) ? baseCount + 1 : baseCount;\n\t\t\t\t\tfullCount = Math.max(1, fullCount);\n\t\t\t\t\tvar fullWidth = (available - (fullCount - 1) * gap) \/ fullCount;\n\t\t\t\t\tif (!isFinite(fullWidth) || fullWidth <= 0){ fullWidth = BASE; }\n\n\t\t\t\t\t\/\/ One or two cards should never grow just because the row is wide.\n\t\t\t\t\t\/\/ They keep the base width, sit at the left, and leave the rest of the row empty.\n\t\t\t\t\tif (totalCards < 3){\n\t\t\t\t\t\tvar smallMax = (available - (totalCards - 1) * gap) \/ totalCards;\n\t\t\t\t\t\tvar smallWidth = (isFinite(smallMax) && smallMax > 0) ? Math.min(BASE, smallMax) : BASE;\n\t\t\t\t\t\treturn { count: totalCards, width: smallWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\t\/\/ If there are fewer cards than a full row would hold, keep the full-row\n\t\t\t\t\t\/\/ card width rather than stretching those few across the whole row, and\n\t\t\t\t\t\/\/ leave the remaining slots empty. Left-aligned, as the master grid is.\n\t\t\t\t\tif (totalCards < fullCount){\n\t\t\t\t\t\treturn { count: totalCards, width: fullWidth, center: false };\n\t\t\t\t\t}\n\n\t\t\t\t\tvar count = Math.min(fullCount, totalCards);\n\t\t\t\t\treturn { count: count, width: fullWidth, center: false };\n\t\t\t\t};\n\t\t\t\t\/\/ Centre the chevrons on the media block of a card rather than on\n\t\t\t\t\/\/ the whole card: on people cards that is the square photo\n\t\t\t\t\/\/ (whose height tracks the fluid card width, so it cannot be\n\t\t\t\t\/\/ expressed in CSS), on project cards the icon block. Published\n\t\t\t\t\/\/ as a custom property the stylesheet reads.\n\t\t\t\twindow.nspTrackPadX = function(track){\n\t\t\t\t\tvar cs = window.getComputedStyle(track);\n\t\t\t\t\treturn (parseFloat(cs.paddingLeft) || 0) + (parseFloat(cs.paddingRight) || 0);\n\t\t\t\t};\n\t\t\t\twindow.nspSyncNav = function(wrap){\n\t\t\t\t\t\/\/ People cards anchor on the photo, which is the visual mass of\n\t\t\t\t\t\/\/ the card. Project cards have no photo -- only a small icon\n\t\t\t\t\t\/\/ at the top -- so they anchor on the card panel itself and\n\t\t\t\t\t\/\/ the arrows land on its vertical centre. Measuring against\n\t\t\t\t\t\/\/ the wrap in viewport coordinates absorbs the track padding\n\t\t\t\t\t\/\/ and card margins without restating any of them here.\n\t\t\t\t\tvar media = wrap.querySelector(\".nsp-card-photo\")\n\t\t\t\t\t\t|| wrap.querySelector(\".nsp-card\");\n\t\t\t\t\tif (!media){ return; }\n\t\t\t\t\tvar r = media.getBoundingClientRect();\n\t\t\t\t\tif (!r.height){ return; }\n\t\t\t\t\tvar w = wrap.getBoundingClientRect();\n\t\t\t\t\twrap.style.setProperty(\"--nsp-nav-top\", ((r.top - w.top) + r.height \/ 2) + \"px\");\n\t\t\t\t};\n\t\t\t}\n\t\t\tvar wrap = document.currentScript.previousElementSibling;\n\t\t\tif(!wrap){ return; }\n\t\t\t\/\/ The frame carries the visible panel, so it has to be revealed\n\t\t\t\/\/ together with the wrap -- otherwise an empty framed box paints\n\t\t\t\/\/ before the cards have been sized into it.\n\t\t\tfunction reveal(w){\n\t\t\t\tw.style.visibility = \"visible\";\n\t\t\t\tvar f = w.parentNode;\n\t\t\t\tif (f && f.classList && f.classList.contains(\"nsp-frame\")){ f.style.visibility = \"visible\"; }\n\t\t\t}\n\t\t\tvar baseWidth = parseInt(wrap.getAttribute(\"data-base-width\"), 10) || window.NSP_BASE_CARD_WIDTH;\n\t\t\tvar track = wrap.querySelector(\".nsp-carousel\");\n\t\t\tvar cards = track ? track.querySelectorAll(\".nsp-card\") : [];\n\t\t\tif(!track || !cards.length){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\/\/ Read from the stylesheet rather than restating it: a hard-coded copy\n\t\t\t\/\/ here is exactly how the gutter drifted from the CSS before.\n\t\t\tvar gap = parseFloat(window.getComputedStyle(track).columnGap) || 24;\n\t\t\tif (!window.nspIsFluidWidth()) {\n\t\t\t\t\/\/ Mobile: unchanged -- fixed per-card width (CSS 82vw), just avoid a partial\n\t\t\t\t\/\/ card peeking out at the wrap edge.\n\t\t\t\tvar cardW = cards[0].getBoundingClientRect().width;\n\t\t\t\tif(!cardW){ if (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap); return; }\n\t\t\t\t\/\/ clientWidth is the PADDING box, so the track padding has to come\n\t\t\t\t\/\/ off before this is the room the cards actually get.\n\t\t\t\tvar available0 = track.clientWidth - window.nspTrackPadX(track);\n\t\t\t\tvar fitCount = Math.max(1, Math.floor((available0 + gap) \/ (cardW + gap)));\n\t\t\t\tvar count0 = Math.min(fitCount, cards.length);\n\t\t\t\tvar needed0 = count0 * cardW + (count0 - 1) * gap;\n\t\t\t\tvar ws0 = window.getComputedStyle(wrap);\n\t\t\t\tvar padX0 = (parseFloat(ws0.paddingLeft) || 0) + (parseFloat(ws0.paddingRight) || 0);\n\t\t\t\tvar target0 = needed0 + window.nspTrackPadX(track) + (ws0.boxSizing === \"border-box\" ? padX0 : 0);\n\t\t\t\twrap.style.maxWidth = Math.ceil(target0) + \"px\";\n\t\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\t\/\/ Desktop\/tablet: fluid card width, filling the row exactly either way.\n\t\t\t\/\/ clientWidth is the PADDING box -- take the track padding off it.\n\t\t\tvar available = track.clientWidth - window.nspTrackPadX(track);\n\t\t\tvar layout = window.nspComputeLayout(available, gap, cards.length, baseWidth);\n\t\t\tfor (var i = 0; i < cards.length; i++){ cards[i].style.flex = \"0 0 \" + layout.width + \"px\"; }\n\t\t\tif (layout.center) {\n\t\t\t\tvar totalW = layout.count * layout.width + (layout.count - 1) * gap;\n\t\t\t\twrap.style.maxWidth = Math.ceil(totalW + window.nspTrackPadX(track)) + \"px\";\n\t\t\t\twrap.style.marginLeft = \"auto\";\n\t\t\t\twrap.style.marginRight = \"auto\";\n\t\t\t}\n\t\t\tif (window.nspSyncNav){ window.nspSyncNav(wrap); }\n\t\t\treveal(wrap);\n\t\t})();<\/script><\/div><noscript><style>.nsp-carousel-wrap,.nsp-frame{visibility:visible !important;}<\/style><\/noscript><div class=\"nsp-popups\" hidden><template class=\"nsp-popup-tpl\" data-id=\"10\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe035;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">International Process Digitalization in Facility Management<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Supported the transformation and standardization of international facility management processes by designing scalable end-to-end process and service structures. <\/p>\n<p>The project included gathering and harmonizing requirements across multiple country organizations, translating business needs into digital process and system solutions, and coordinating international rollouts including SIT, UAT, training, and change management. <\/p>\n<p>Consistent process modeling and documentation using BPMN 2.0 and SAP Signavio helped establish sustainable governance, transparency, and operational efficiency.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>SAP Signavio, BPMN 2.0, ERP Systems, Digital Workflow Platforms, Interface Integration, SIT\/UAT, Requirements Management<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tHuman-Technology Interaction\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"11\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<span class=\"nsp-pop-icon et-pb-icon\" aria-hidden=\"true\">&#xe00d;<\/span>\t\t\t\t<span class=\"nsp-dlg-h-title\">ERP\/CRM Product Development &amp; Process Digitalization<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>Led the development and implementation of a modular ERP\/CRM system to digitalize central business processes.<\/p>\n<p>The project included end-to-end product ownership, requirements analysis, prioritization, and scaling of the system, including mobile solutions and extensions.<\/p>\n<p>Responsibilities also covered the management of cross-functional development teams, the establishment of testing, quality, and operations processes, and the introduction of ITIL-based change and incident structures. Governance, KPI, PMO, and documentation standards were developed to support sustainable product and project management, while product strategy and stakeholder alignment were managed at leadership level.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>ERP\/CRM Systems, Mobile Solutions, Agile Product Development, Requirements Management, UAT, ITIL, Change &amp; Incident Management, KPI\/PMO Structures, Stakeholder Management<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/control-and-automation\">Automation<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/data-and-knowledge-management\/\">Data Warehouse<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tHuman-Technology Interaction\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"13\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Search Recommendations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For VisualSearch, the focus was on developing and deploying e-commerce plugins to enhance recommendation functionalities in web shops. The plugins were successfully launched in the store and happily adopted by customers, demonstrating their practical use in improving e-commerce experiences. Key elements included:<br \/>\n- computation of visual embeddings from appearances of e-commerce products<br \/>\n- building and maintaining a search index using these embeddings<br \/>\n- providing a cloud-based API for Shopware and Prestashop plugins<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"369\" height=\"455\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch.png 369w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/visualsearch-10x12.png 10w\" sizes=\"(max-width: 369px) 100vw, 369px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, leveraging AWS services, Python, and deep learning frameworks like Keras. The project integrated cloud-based solutions using CloudFormation, Lambda, and Gateway for scalable and efficient deployment, using SQL and DynamoDB for data management.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"14\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Visual Assistance for Seniors<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For the Austrian Institute of Technology (as a part of the national research project LARAH), a prototype of an assistance system for visual indoor localization for disabled and elderly persons was developed. By leveraging Computer Vision and Deep Learning, innovative algorithms for position determination were implemented. The project resulted in a functional prototype, including two Android applications for real-time localization. Key elements included:<br \/>\n- visual recognition of persons using Deep-Learning models<br \/>\n- visual reconstruction and localization of indoor environments using Structure-from-Motion and Machine Learning algorithms<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"366\" height=\"451\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah.png 366w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-243x300.png 243w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/larah-10x12.png 10w\" sizes=\"(max-width: 366px) 100vw, 366px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>Peter acted as the project manager and key data scientist on this project, developed under Python using Deep Learning models like TensorFlow, custom-developed Structure-from-Motion software and custom camera calibration software. Additionally, as a part of the project, two Android apps were modified and integrated together onto the Robot Operating System on the mobile platform.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"1\">\t\t<div class=\"nsp-dialog has-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t\t\t\t\t<span class=\"nsp-dlg-h-title\">Electrical Switch Monitor<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><p>For a public transportation network, the objective was to optimize the monitoring of their legacy electrical switchboards. These decade-old items that are often located in very remote areas are prone to failures and tracking of errors was not possible. The objective was to enable real-time tracking and the recognition of upcoming failures from changed switching behavior. The key elements were:<\/p>\n<ul>\n<li>Development of specific hardware configuration with custom housings (3D printed) to mount instead of regular switchboard covers;<\/li>\n<li>Camera control and initial image generation on Raspberry Pi integrated in housing;<\/li>\n<li>Initial scan of switch layout and labels;<\/li>\n<li>Identification of switching operations and registration of new positions;<\/li>\n<li>Identification of irregular switching patterns (delays, other irregularities) to indicate upcoming failures for predictive maintenance;<\/li>\n<li>Update of central database and cloud solution with last state and observed switching patterns;<\/li>\n<\/ul>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-aside\">\n\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"959\" src=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-1024x959.jpg\" class=\"nsp-pop-img\" alt=\"\" srcset=\"https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-980x918.jpg 980w, https:\/\/www.9senses.ai\/wp-content\/uploads\/2026\/07\/6by6cropped-480x450.jpg 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1024px, 100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--aside\"><p>The solution was implemented using Python on Raspberry Pi devices, backbone and cloud processing were done using a LAMP stack, with PyTorch, TensorFlow and OpenCV.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><template class=\"nsp-popup-tpl\" data-id=\"5\">\t\t<div class=\"nsp-dialog no-image\">\n\t\t\t<button type=\"button\" class=\"nsp-close\" aria-label=\"Close\">&times;<\/button>\n\t\t\t<div class=\"nsp-dlg-h\">\n\t\t\t\t<i class=\"nsp-pop-icon fa-solid fa-water\" aria-hidden=\"true\"><\/i>\t\t\t\t<span class=\"nsp-dlg-h-title\">Hydropower Plant Operations<\/span>\n\t\t\t<\/div>\n\t\t\t<div class=\"nsp-pop-cols\">\n\t\t\t\t<div class=\"nsp-pop-main\">\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-desc\"><div class=\"et_pb_column_11 et_pb_column et_flex_column et_pb_css_mix_blend_mode_passthrough et_flex_column_6_24 et_flex_column_12_24_tablet et_flex_column_24_24_phone et_flex_column_12_24_tabletWide preset--group--divi-column--divi-box-shadow--default preset--group--divi-column--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_2 et_pb_blurb et_pb_bg_layout_light et_pb_blurb_position_top et_pb_module et_flex_module hovergroup preset--group--divi-blurb--divi-box-shadow--default preset--group--divi-blurb--divi-font-body--h19rs5u--7p5s44libg preset--group--divi-blurb--divi-sizing--hsj9uxo--default\">\n<div class=\"et_pb_blurb_content et_flex_module\">\n<div class=\"et_pb_blurb_container\">\n<div class=\"et_pb_blurb_description\">\n<p>Create an integrated monitoring and surveillance solution for small-scale hydropower plants in remote locations. The solution included a full range of required settings:<\/p>\n<ul>\n<li>real-time monitoring and logging of operations<\/li>\n<li>failure detection and automated<\/li>\n<li>predictive maintenance logic to identify early failure<\/li>\n<li>camera-based intrusion and irregularity detection<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"nsp-pop-role nsp-pop-role--below\"><p>The solution was a hybrid solution using Siemens PLCs, combined with small edge computing elements (Raspberry Pi and Arduino). All primary logic (particularly shutdown and load adjustment) was local, but key decisions and aggregations were executed online based on regular data transmission to a cloud-based management and operations suite.<\/p>\n<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t<ul class=\"nsp-chiplist nsp-pop-caps\">\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/machine-learning\">Machine Learning<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/vision\">Computer Vision<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<li class=\"nsp-chip\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"\/automation-and-control\">Infrastructure Management<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t<\/div>\n\t\t<\/template><\/div><div class=\"nsp-overlay\" id=\"nsp-overlay\" role=\"dialog\" aria-modal=\"true\"><\/div><\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_8 et_pb_section et_section_regular et_flex_section ns-panel\" id=\"robotics\" style=\"--ns-rail-w:264px; --ns-body-color:#D3D3D3;\">\n<div class=\"et_pb_row_14 et_pb_row et_flex_row\">\n<div class=\"et_pb_column_22 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_13 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><p><span>Of all AI fields, robotics is the one where software has consequences in the physical world: sensor data has to be turned into safe, precise motion in real time, and there is no undo button. That step from calculating to acting is what makes the field so demanding, and why progress here is slower than in purely digital AI.<\/span><\/p>\n<\/div><\/div>\n\n<div class=\"et_pb_code_8 et_pb_code et_pb_module\"><div class=\"et_pb_code_inner\">\t<div\n\t\tid=\"ns-aix-4\"\n\t\tclass=\"ns-aix ns-aix-rob ns-aix-rob3d\"\n\t\tdata-topic=\"rob\"\n\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\tdata-journey=\"industrial\"\n\t\tdata-active-key=\"task\"\n\t\t\t\tdata-step=\"0\"\n\t\tdata-interval=\"9000\"\n\t\t\t\tdata-autoplay=\"1\"\n\t\trole=\"region\"\n\t\taria-label=\"So funktioniert Robotik\"\n\t\tstyle=\"--ns-aix-accent:#58a7f9;--ns-aix-secondary:#2b6cb0\"\n\t>\n\t\t<header class=\"ns-aix-head\">\n\t\t\t\t\t\t<h3 class=\"ns-aix-title\">So funktioniert Robotik<\/h3>\n\t\t\t<p class=\"ns-aix-intro\">In der Robotik werden KI und Automatisierung physisch. Sensoren vermessen die Welt, Software sch\u00e4tzt, was geschieht, Steuerungen w\u00e4hlen sichere Bewegung, und Aktoren bewegen reale Objekte. Der Kreislauf funktioniert nur, wenn Sicherheit, Verifikation und Governance von Anfang an eingeplant sind.<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-flowgroup ns-aix-flowgroup-shaped\">\n\t\t\t\t\t\t\t\t\t\t\t<svg class=\"ns-aix-flowshape\" aria-hidden=\"true\" focusable=\"false\" preserveAspectRatio=\"none\">\n\t\t\t\t\t\t\t<path class=\"ns-aix-flowshape-fill\" d=\"\" \/>\n\t\t\t\t\t\t\t<path class=\"ns-aix-flowshape-glow\" d=\"\" \/>\n\t\t\t\t\t\t<\/svg>\n\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-tabs\" role=\"tablist\" aria-label=\"So funktioniert Robotik\">\n\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\tid=\"ns-aix-4-tab-industrial\"\n\t\t\t\t\t\t\tclass=\"ns-aix-tab ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"true\"\n\t\t\t\t\t\t\taria-label=\"Den Weg der industriellen Roboterzelle anzeigen\"\n\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\taria-controls=\"ns-aix-4-flow-panel-industrial\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\tIndustrieroboter\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\tid=\"ns-aix-4-tab-autonomous\"\n\t\t\t\t\t\t\tclass=\"ns-aix-tab\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\trole=\"tab\"\n\t\t\t\t\t\t\taria-selected=\"false\"\n\t\t\t\t\t\t\taria-label=\"Den Weg des autonomen Roboters anzeigen\"\n\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\taria-controls=\"ns-aix-4-flow-panel-autonomous\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\tAutonomer Roboter\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-flow-intros\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p\n\t\t\t\t\t\t\t\tid=\"ns-aix-4-flow-intro-industrial\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-flow-intro ns-on\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\tEin Fabrikroboter kann sehr leistungsf\u00e4hig sein, weil die Roboterzelle bewusst eingeschr\u00e4nkt ist. Vorrichtungen, Koordinaten, Werkzeuge, Geschwindigkeitsgrenzen und Schutzbereiche reduzieren die Unsicherheit, bevor die Steuerung den Roboter \u00fcberhaupt bewegt.\t\t\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p\n\t\t\t\t\t\t\t\tid=\"ns-aix-4-flow-intro-autonomous\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-flow-intro\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\tAutonomie wird schwieriger, sobald die Grenzen wegfallen. Ein Fahrzeug, Rover oder Laufroboter muss seine eigene Position sch\u00e4tzen, eine sich ver\u00e4ndernde Szene deuten und unter Unsicherheit sicher handeln.\t\t\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/header>\n\n\t\t<div class=\"ns-aix-body\">\n\t\t\t<div class=\"ns-aix-copy\">\n\t\t\t\t<div class=\"ns-aix-progress\" aria-hidden=\"true\"><span><\/span><\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-4-flow-panel-industrial\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel ns-on\"\n\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\trole=\"tabpanel\" aria-labelledby=\"ns-aix-4-tab-industrial\"\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps ns-on\" data-flow=\"industrial\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step ns-on\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"task\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Aufgabe<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Eine klar abgegrenzte Aufgabe macht Automatisierung m\u00f6glich.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"sense\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Erfassen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Kameras, Encoder und Kraftsignale gehen in den Regelkreis ein.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"locate\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Lokalisieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Position z\u00e4hlt nur in einem gemeinsamen Bezugssystem.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"plan\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Planen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Eine Route wird gew\u00e4hlt, bevor die Bewegung beginnt.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"control\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Regeln<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Aktoren machen aus Befehlen Bewegung.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"verify\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verifizieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Erfolg wird gemessen, nicht angenommen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"protect\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Sch\u00fctzen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Physisches Handeln braucht ausdr\u00fcckliche Grenzen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\t\tdata-key=\"improve\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-7\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">08<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verbessern<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Protokolle st\u00fctzen Wartung und Optimierung.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div\n\t\t\t\t\t\tid=\"ns-aix-4-flow-panel-autonomous\"\n\t\t\t\t\t\tclass=\"ns-aix-step-panel\"\n\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\trole=\"tabpanel\" aria-labelledby=\"ns-aix-4-tab-autonomous\"\t\t\t\t\t>\n\t\t\t\t\t<ol class=\"ns-aix-steps\" data-flow=\"autonomous\" role=\"list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\t\tdata-key=\"mission\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-0\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">01<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Auftrag<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Ein Auftrag umfasst Regeln, nicht nur ein Ziel.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\t\tdata-key=\"perceive\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-1\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">02<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Wahrnehmen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Mehrere Sensoren verringern blinde Flecken.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\t\tdata-key=\"localize\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-2\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">03<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Verorten<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Die Karte n\u00fctzt nur mit einer laufenden Posensch\u00e4tzung.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\t\tdata-key=\"model\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-3\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">04<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Modellieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Objekte, Raum und Risiko werden gesch\u00e4tzt.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\t\tdata-key=\"plan\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-4\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">05<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Planen<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">M\u00f6gliche Bahnen konkurrieren unter Randbedingungen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\t\tdata-key=\"act\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-5\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">06<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Handeln<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Die Bewegungsregelung passt sich fortlaufend an.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\t\tdata-key=\"respond\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-6\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">07<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Reagieren<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Der R\u00fcckfall ist Teil der Autonomie.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\t\tclass=\"ns-aix-step\"\n\t\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\t\tdata-key=\"govern\"\n\t\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-7\"\n\t\t\t\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-num\">08<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-text\">\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-label\">Steuern<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"ns-aix-step-micro\">Protokolle, Grenzen und menschliches Eingreifen z\u00e4hlen.<\/span>\n\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t<\/ol>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\n\t\t\t<div class=\"ns-aix-stage\" aria-label=\"Animiertes Vektorkarten-Prozessdiagramm\">\n\t\t\t\t<canvas class=\"ns-aix-canvas\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t<canvas class=\"ns-aix-canvas3d\" aria-hidden=\"true\"><\/canvas>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-on\" data-flow=\"industrial\" data-step=\"0\" data-key=\"task\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>aufgabe<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"1\" data-key=\"sense\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>erfassen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"2\" data-key=\"locate\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>bildfolge<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"3\" data-key=\"plan\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>plan<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"4\" data-key=\"control\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>handeln<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"5\" data-key=\"verify\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pr\u00fcfen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"6\" data-key=\"protect\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>sicherheit<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node\" data-flow=\"industrial\" data-step=\"7\" data-key=\"improve\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>protokolle<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"0\" data-key=\"mission\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>auftrag<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"1\" data-key=\"perceive\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>erfassen<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"2\" data-key=\"localize\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>pose<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"3\" data-key=\"model\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>szene<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"4\" data-key=\"plan\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>plan<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"5\" data-key=\"act\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>handeln<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"6\" data-key=\"respond\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>r\u00fcckfall<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t<button type=\"button\" class=\"ns-aix-node ns-hidden\" data-flow=\"autonomous\" data-step=\"7\" data-key=\"govern\" tabindex=\"-1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t<span>steuern<\/span>\n\t\t\t\t\t\t<\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t<\/div>\n\n\t\t<div class=\"ns-aix-controls\">\n\t\t\t<div class=\"ns-aix-dots\" role=\"navigation\" aria-label=\"Schrittnavigation\">\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset ns-on\"\n\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr Industrieroboter\"\n\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot ns-on\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Aufgabe\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"true\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Erfassen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Lokalisieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Planen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Regeln\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Verifizieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Sch\u00fctzen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 8: Verbessern\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-industrial-7\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"0\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span\n\t\t\t\t\t\tclass=\"ns-aix-dotset\"\n\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\trole=\"group\"\n\t\t\t\t\t\taria-label=\"Schritte f\u00fcr Autonomer Roboter\"\n\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 1: Auftrag\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-0\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 2: Wahrnehmen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-1\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 3: Verorten\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-2\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 4: Modellieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-3\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 5: Planen\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-4\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 6: Handeln\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-5\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 7: Reagieren\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-6\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<button\n\t\t\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t\t\t\tclass=\"ns-aix-dot\"\n\t\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\t\taria-label=\"Schritt 8: Steuern\"\n\t\t\t\t\t\t\t\taria-controls=\"ns-aix-4-panel-autonomous-7\"\n\t\t\t\t\t\t\t\taria-pressed=\"false\"\n\t\t\t\t\t\t\t\ttabindex=\"-1\"\n\t\t\t\t\t\t\t><\/button>\n\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\n\t\t<div class=\"ns-aix-below\" aria-live=\"polite\">\n\t\t\t<div class=\"ns-aix-explain\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel ns-on\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"false\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Die physische Aufgabe definieren<\/h4>\n\t\t\t\t\t\t\t<p>Industrierobotik beginnt mit einer definierten Aufgabe: greifen, ablegen, schwei\u00dfen, pr\u00fcfen, schrauben, verpacken oder sortieren. Die Umgebung wird um die Aufgabe herum gestaltet, damit der Roboter nicht die ganze Welt verstehen muss. Werkst\u00fcck, Vorrichtung, Werkzeug und erlaubte Bahn sind festgelegt, bevor die Automatisierung beginnt.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>Die Roboterzelle vermessen<\/h4>\n\t\t\t\t\t\t\t<p>Sensoren sagen der Steuerung, ob die Realit\u00e4t zum Programm passt. Kameras lokalisieren Teile, Encoder melden Gelenkstellungen, Kraftsensoren erkennen Kontakt, und Sicherheitssensoren erkennen Menschen oder Hindernisse. Ohne Sensorik kann der Roboter nur feste Bewegungen wiederholen und hoffen, dass sich die Szene nicht ver\u00e4ndert hat.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Hinweise in Koordinaten \u00fcberf\u00fchren<\/h4>\n\t\t\t\t\t\t\t<p>Der Roboter muss wissen, wo das Teil relativ zu Kamera, F\u00f6rderband, Vorrichtung, Werkzeug und Roboterbasis liegt. Die Kalibrierung \u00fcberf\u00fchrt Sensordaten in ein gemeinsames Koordinatensystem.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Eine sichere Bahn w\u00e4hlen<\/h4>\n\t\t\t\t\t\t\t<p>Die Bahnplanung berechnet, wie der Roboter von seiner aktuellen Pose zur Zielpose gelangen soll. Sie muss Gelenkgrenzen, Traglast, Erreichbarkeit, Werkzeugorientierung, Vorrichtungen, Taktzeit und Kollisionsr\u00e4ume einhalten.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Mit R\u00fcckmeldung bewegen<\/h4>\n\t\t\t\t\t\t\t<p>Motoren, Antriebe, Ventile und Greifer f\u00fchren die geplante Bewegung aus. Regelkreise vergleichen viele Male pro Sekunde Soll- und Ist-Bewegung und korrigieren Position, Geschwindigkeit, Drehmoment oder Kraft. Hier wird aus Software physisches Verhalten.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Das Ergebnis pr\u00fcfen<\/h4>\n\t\t\t\t\t\t\t<p>Ein Roboter sollte nicht davon ausgehen, dass die Aufgabe gelungen ist. Kameras, Drehmomentverl\u00e4ufe, Kraftkurven, Gewichtspr\u00fcfungen oder nachgelagerte Qualit\u00e4tsstationen best\u00e4tigen, ob das Teil korrekt gegriffen, abgelegt, verschraubt, gemessen oder aussortiert wurde.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Begrenzen, was passieren darf<\/h4>\n\t\t\t\t\t\t\t<p>Robotik erzeugt physisches Risiko. Schutzbereiche, Geschwindigkeitsgrenzen, Kraftbegrenzung im kollaborativen Betrieb, Not-Halt, Wartungsmodi und menschliches Eingreifen legen fest, was die Maschine darf. Sicherheit ist kein Zusatz zur Robotik; sie ist Teil der Steuerung.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-industrial-7\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"industrial\"\n\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">08<\/span>Aus dem Betrieb lernen<\/h4>\n\t\t\t\t\t\t\t<p>Taktzeiten, fehlgeschlagene Griffe, Qualit\u00e4tsergebnisse, Sensorverl\u00e4ufe und Wartungsdaten k\u00f6nnen das System verbessern \u2013 \u00fcber besseres Werkzeug, aktualisierte Regeln, vorausschauende Wartung oder Machine-Learning-Modelle. Jede Verbesserung sollte von einer Ingenieurin validiert, protokolliert und neu qualifiziert werden, bevor sie die Bewegung beeinflusst.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-0\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"0\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">01<\/span>Ziel und Grenzen festlegen<\/h4>\n\t\t\t\t\t\t\t<p>Ein autonomer Roboter braucht mehr als ein Ziel. Er braucht einen definierten Einsatzbereich: wo er sich bewegen darf, wie nah er Menschen kommen darf, wann er langsamer werden muss, welche Bedingungen au\u00dferhalb seiner Auslegungsgrenzen liegen und wann ein Mensch \u00fcbernehmen muss.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-1\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"1\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">02<\/span>Die Umgebung erfassen<\/h4>\n\t\t\t\t\t\t\t<p>Kameras, Lidar, Radar, Ultraschallsensoren, GPS, Inertialsensoren, Radencoder oder taktile Sensoren liefern jeweils nur Teilinformationen. Jeder Sensor hat Ausfallmuster: Blendung, Regen, Staub, Verdeckung, Reflexionen, schlechte Beleuchtung, schwaches GPS oder Vibration.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-2\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"2\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">03<\/span>Position und Unsicherheit sch\u00e4tzen<\/h4>\n\t\t\t\t\t\t\t<p>Der Roboter muss sch\u00e4tzen, wo er ist, wie schnell er sich bewegt und wie sicher diese Sch\u00e4tzung ist, indem er laufende Sensordaten mit einer gespeicherten Karte abgleicht oder unterwegs eine aufbaut. Sinkt die Verl\u00e4sslichkeit der Ortung, sollte das Verhalten vorsichtiger werden.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-3\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"3\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">04<\/span>Ein belastbares Szenenmodell aufbauen<\/h4>\n\t\t\t\t\t\t\t<p>Aus Sensordaten wird ein strukturiertes Weltmodell: freier Raum, Hindernisse, Menschen, Fahrzeuge, T\u00fcren, Bordsteine, Treppen, Gel\u00e4nde und bewegte Objekte. Das System muss au\u00dferdem vorhersagen, wohin sich bewegende Akteure als N\u00e4chstes wahrscheinlich bewegen.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-4\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"4\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">05<\/span>Die n\u00e4chste Bewegung w\u00e4hlen<\/h4>\n\t\t\t\t\t\t\t<p>Planung findet auf mehreren Ebenen statt: Routenplanung, lokale Bahnplanung, Hindernisvermeidung, Geschwindigkeitswahl und R\u00fcckfallverhalten. Das System sollte nicht nur fragen, ob es das Ziel erreichen kann, sondern ob es das unter der aktuellen Unsicherheit sicher erreichen kann.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-5\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"5\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">06<\/span>Den K\u00f6rper regeln<\/h4>\n\t\t\t\t\t\t\t<p>Der Plan wird \u00fcber Motoren, Bremsen, Lenkung, R\u00e4der, Beine oder Gelenke zur Bewegung. Ein Fahrzeug regelt Lenkung, Beschleunigung und Bremsen. Ein Laufroboter muss zus\u00e4tzlich balancieren, F\u00fc\u00dfe setzen und ungleichm\u00e4\u00dfigen Kontakt bew\u00e4ltigen. R\u00fcckmeldung h\u00e4lt Soll- und Ist-Bewegung im Einklang.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-6\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"6\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">07<\/span>Mit \u00dcberraschungen umgehen<\/h4>\n\t\t\t\t\t\t\t<p>Robotik in der offenen Welt zeigt sich an \u00dcberraschungen: Eine Person tritt in die Bahn, ein Sensor wird geblendet, der Boden wird rutschig oder ein anderes Fahrzeug verh\u00e4lt sich unvorhersehbar. Sichere Autonomie bedeutet: langsamer werden, anhalten, umplanen, Hilfe anfordern oder die Kontrolle an einen Menschen \u00fcbergeben.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t<section\n\t\t\t\t\t\t\tid=\"ns-aix-4-panel-autonomous-7\"\n\t\t\t\t\t\t\tclass=\"ns-aix-panel\"\n\t\t\t\t\t\t\tdata-flow=\"autonomous\"\n\t\t\t\t\t\t\tdata-step=\"7\"\n\t\t\t\t\t\t\taria-hidden=\"true\"\n\t\t\t\t\t\t>\n\t\t\t\t\t\t\t<h4><span class=\"ns-aix-panel-num\">08<\/span>Belegen, dass die Autonomie kontrolliert ist<\/h4>\n\t\t\t\t\t\t\t<p>Autonome Roboter brauchen Protokolle, Sicherheitsnachweise, Grenzen des Einsatzbereichs, Update-Kontrolle, Cybersicherheit, Datenschutzregeln, menschliches Eingreifen und gekl\u00e4rte Haftung. Weil KI-gesteuertes Verhalten schwerer nachzuvollziehen ist als konventionelle Logik, muss Governance um den Roboter herum aufgebaut werden, bevor man ihm physisches Handeln anvertraut.<\/p>\n\t\t\t\t\t\t<\/section>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"ns-aix-aspects\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset ns-on\" data-flow=\"industrial\" data-step=\"0\" aria-hidden=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Hintergrund<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die ersten Industrieroboter kamen in den 1960er-Jahren f\u00fcr wiederkehrende Aufgaben wie Schwei\u00dfen und Montage in die Produktion; Sensorik und Planung machten sp\u00e4ter aus starren Armen anpassungsf\u00e4hige Systeme.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Robotik verbindet Mechanik, Elektronik und Software: Sensoren zum Wahrnehmen, Aktoren zum Handeln und eine Steuerung zum Koordinieren.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein Roboter durchl\u00e4uft viele Male pro Sekunde einen fortlaufenden Zyklus aus Wahrnehmen, Planen und Handeln.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Kameras, Encoder, Kraft- und Sicherheitssensoren beantworten jeweils eine andere Frage zur Szene \u2013 zusammen ersetzen sie Vermutung durch Evidenz.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Kalibrierung verbindet Kamera, F\u00f6rderband, Werkzeug und Roboterbasis zu einem gemeinsamen Koordinatensystem \u2013 die Br\u00fccke von der Wahrnehmung zur Bewegung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein kleiner Kalibrierfehler kann zu einem fehlgeschlagenen Griff, einer schlechten Schwei\u00dfnaht, einer Kollision oder einem Qualit\u00e4tsmangel werden.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>M\u00f6gliche Bahnen werden gegen Gelenkgrenzen, Traglast, Reichweite, Werkzeugorientierung, Vorrichtungen und Kollisionsr\u00e4ume gepr\u00fcft, bevor eine reale Bewegung startet.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Der brauchbare Weg ist nicht einfach der k\u00fcrzeste; es ist der Weg, der sicher und wiederholbar ausgef\u00fchrt werden kann.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Servoregelung l\u00e4uft tausende Male pro Sekunde: Jeder Zyklus misst den Gelenkzustand und korrigiert die Antriebe \u2013 deshalb wirkt industrielle Bewegung fl\u00fcssig und sitzt wiederholgenau.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Bei einfachen Industrierobotern sind Bewegungen vorprogrammiert und werden pr\u00e4zise wiederholt; fortgeschrittene Systeme passen sich mit maschinellem Lernen und Echtzeit-R\u00fcckmeldung an ver\u00e4nderte Bedingungen an.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Verifikation macht aus blinder Automatisierung einen kontrollierten Prozess \u2013 jeder Zyklus erzeugt Nachweise statt Annahmen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Eine fehlgeschlagene Pr\u00fcfung kann einen automatischen Wiederholversuch ausl\u00f6sen, das Teil ausschleusen oder die Linie stoppen \u2013 die Reaktion auf schlechte Evidenz ist im Voraus geplant, nicht improvisiert.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Der Sicherheitsrahmen hat Vorrang vor der Produktionsgeschwindigkeit: Zonen, Grenzen, Not-Halt und menschliches Eingreifen sind in die Steuerung selbst eingebaut.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Mechanischer Verschlei\u00df, Batteriegrenzen und Systemausf\u00e4lle bergen physische Risiken f\u00fcr Menschen und Anlagen und erfordern laufende Wartung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"industrial\" data-step=\"7\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Was Robotik leisten kann<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Wiederkehrende, gef\u00e4hrliche und hochpr\u00e4zise Aufgaben; Transport im Lager; Staubsaugen in Wohnungen; Erkundung gef\u00e4hrlicher oder weit entfernter R\u00e4ume.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Autonomie in der offenen Welt bleibt schwierig: unter allen Bedingungen zu fahren wie ein Mensch oder die Geschicklichkeit eines Kindes in einem Humanoiden zu erreichen, ist weiterhin eine gro\u00dfe und teure Herausforderung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"0\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das Ziel wird durch den Einsatzbereich begrenzt \u2013 Autonomie ohne ausdr\u00fcckliche Grenzen ist kein Entwurf, sondern eine Gefahr.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Navigation im offenen Raum, etwa auf Stra\u00dfen oder im Gel\u00e4nde, bleibt eines der schwersten Probleme der Robotik und verlangt erhebliche Sensorik und Rechenleistung.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"1\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Sensoren erfassen Daten zu Abstand, Position, Temperatur oder Bildinhalt; die Steuerung f\u00fchrt diese Hinweise zu einem Bild der Umgebung zusammen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Sensordaten sind n\u00fctzlich, aber nie perfekt \u2013 robuste Systeme rechnen mit beeintr\u00e4chtigter Eingabe und gleichen Sensoren gegeneinander ab.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"2\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>GPS, Odometrie, Inertialsensoren, Landmarken, Lidar und visuelle Merkmale werden kombiniert \u2013 und k\u00f6nnen sich widersprechen; die Sch\u00e4tzung tr\u00e4gt eine Unsicherheit, keine Gewissheit.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Unsicherheit muss in die Entscheidungen einflie\u00dfen: Ein Roboter, der ausblendet, wie unsicher er ist, handelt mit falscher Zuversicht.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"3\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Das Szenenmodell ist eine sich ver\u00e4ndernde Sch\u00e4tzung, mit der entschieden wird, welche Bewegung sicher bleibt \u2013 kein perfektes Verst\u00e4ndnis der Welt.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein Lagerroboter nutzt dieses Modell, um Hindernissen auszuweichen, w\u00e4hrend er einen Zielort ansteuert.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"4\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Bahnplanungsalgorithmen lassen einen Roboter sicher navigieren, oft kombiniert mit Bildverarbeitung zur Objekterkennung und maschinellem Lernen zur Verbesserung \u00fcber die Zeit.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Unsichere Bahnvarianten m\u00fcssen ausscheiden, bevor die Bewegung beginnt \u2013 in der Planung wird das Risiko herausgefiltert.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"5\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>So funktioniert es<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Die Regelung l\u00e4uft viel schneller als die Planung: W\u00e4hrend eine neue Route einige Male pro Sekunde berechnet wird, korrigieren Balance- und Rad- bzw. Gelenkregelung die Bewegung hunderte Male pro Sekunde.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Humanoide Roboter zu bauen, die laufen und ihre H\u00e4nde geschickt einsetzen, ist noch weit von dem entfernt, was schon ein kleines Kind kann.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"6\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Kernkonzept<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Unerwartete Ereignisse sollten vorsichtiges Verhalten ausl\u00f6sen \u2013 der R\u00fcckfall in einen sicheren Zustand ist eine geplante Eigenschaft, kein Versagen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>In der Praxis<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Ein Lieferroboter, der anh\u00e4lt und Unterst\u00fctzung aus der Ferne anfordert, verh\u00e4lt sich richtig \u2013 er versagt nicht.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspectset\" data-flow=\"autonomous\" data-step=\"7\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Warum das z\u00e4hlt<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Kontrollierte Autonomie braucht Nachweise: Ohne Protokolle und Sicherheitsnachweise l\u00e4sst sich Vertrauen in ein physisches KI-System nicht begr\u00fcnden.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"ns-aix-aspect\">\n\t\t\t\t\t\t\t\t\t\t<h5>Achtung<\/h5>\n\t\t\t\t\t\t\t\t\t\t<p>Roboter erfordern erheblichen Engineering-, Wartungs- und Sicherheitsaufwand; Fehler k\u00f6nnen Menschen und Sachen physisch sch\u00e4digen.<\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_23 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tablet et_flex_column_24_24_phone et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_14 et_pb_text et_pb_bg_layout_light et_pb_module et_flex_module\"><div class=\"et_pb_text_inner\"><h3>The Challenges<\/h3>\n<p>Robotics, particularly when it comes to robots navigating an open space like a road or terrain, is still a very difficult field, requiring\u00a0 significant sensing and computing power. Making an autonomous car drive under all conditions like a human driver is still a significant and expensive challenge. And creating humanoid robots that can walk and dextrously use their \"hands\" is still difficult. Today's models are still far away from reaching the overall ability even a child has when it comes to processing sensory input and turning it into smooth and seamless motion.<\/p>\n<p>Robots also require substantial engineering effort, maintenance, and safety considerations. Battery life, mechanical wear, and system failures can limit performance and create risk of physical damage to people and things.<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<div class=\"et_pb_section_9 et_pb_section et_section_regular et_block_section\">\n<div class=\"et_pb_row_15 et_pb_row et_flex_row ns-cta\">\n<div class=\"et_pb_column_24 et_pb_column et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_text_15 et_pb_text et_pb_bg_layout_light et_pb_module et_block_module\"><div class=\"et_pb_text_inner\"><p>Understanding these different AI approaches is essential when designing real-world AI systems. Each method has distinct strengths and limitations, which must be carefully considered when selecting the right approach for a given problem.<\/p>\n<p>If you want to see how we put these approaches to work, <a href=\"\/transformation\/\">move to what we can do for you<\/a>.<\/p>\n<\/div><\/div>\n<\/div>\n\n<div class=\"et_pb_column_25 et_pb_column et-last-child et_block_column et_pb_css_mix_blend_mode_passthrough et_flex_column_24_24 et_flex_column_24_24_tabletWide\">\n<div class=\"et_pb_module et_pb_button_module_wrapper et_pb_button_1_wrapper\"><a class=\"et_pb_button_1 et_pb_button et_pb_bg_layout_light et_pb_module et_block_module\" href=\"\/transformation\/\" style=\"text-wrap:balance\">9senses AI Transformation<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>9senses view on Artificial Intelligence is driven by a realistic view of the opportunities, limits and risks that AI comes with. It is grounded in a view that even though it very well simulates intelligence, it isn&#8217;t consciously intelligent and thus needs oversight.<\/p>","protected":false},"author":15,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_ns_ir":"","_ns_ir_pending":"","_ns_structural_eyebrow":"","_ns_ir_live":"","_ns_structural_enabled":"","_ns_structural_body_v1":"","n9tr_seo_title_de_DE":"Was KI wirklich ist - 9senses.ai","n9tr_seo_description_de_DE":"9senses sieht KI realistisch: Chancen, Grenzen und Risiken. KI simuliert Intelligenz sehr gut, ist aber nicht bewusst intelligent und braucht deshalb Aufsicht.","n9tr_seo_title_fr_FR":"","n9tr_seo_description_fr_FR":"","footnotes":""},"class_list":["post-227133","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/227133","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/comments?post=227133"}],"version-history":[{"count":345,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/227133\/revisions"}],"predecessor-version":[{"id":230176,"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/pages\/227133\/revisions\/230176"}],"wp:attachment":[{"href":"https:\/\/www.9senses.ai\/de\/wp-json\/wp\/v2\/media?parent=227133"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}